diff --git a/data/abcs_gas/README.md b/data/abcs_gas/README.md new file mode 100644 index 000000000..f8c73cdd2 --- /dev/null +++ b/data/abcs_gas/README.md @@ -0,0 +1,15 @@ +# abcs_gas + +This is a dcf data source project, initialized with `dcf::dcf_add_source`. + +You can us the `dcf` package to check the project: + +```R +dcf_check_source("abcs_gas", "..") +``` + +And process it: + +```R +dcf_process("abcs_gas", "..") +``` diff --git a/data/abcs_gas/ingest.R b/data/abcs_gas/ingest.R new file mode 100644 index 000000000..431c69750 --- /dev/null +++ b/data/abcs_gas/ingest.R @@ -0,0 +1,193 @@ +# ============================================================================= +# ABCs Group A Streptococcus Data Ingestion +# Source: https://data.cdc.gov/Public-Health-Surveillance/Active-Bacterial-Core-surveillance-ABCs-Group-A-St/9y49-tura/about_data +# ============================================================================= + +library(dplyr) + +process <- dcf::dcf_process_record() + +raw_state <- dcf::dcf_download_cdc( + "9y49-tura", + "raw", + process$raw_state +) + +if (!identical(process$raw_state, raw_state)) { + + data_raw <- vroom::vroom("raw/9y49-tura.csv.xz", show_col_types = FALSE) %>% + rename( + year = Year, + value = Value, + units = Units, + bacteria = Bacteria, + topic = Topic, + viewby = ViewBy, + viewby2 = ViewBy2 + ) %>% + mutate( + # Normalize casing inconsistencies across years + topic = case_when( + tolower(trimws(topic)) == "case rates" ~ "Case rates", + tolower(trimws(topic)) == "death rates" ~ "Death rates", + tolower(trimws(topic)) == "number of cases and deaths" ~ "Number of cases and deaths", + tolower(trimws(topic)) == "syndromes" ~ "Syndromes", + tolower(trimws(topic)) == "antibiotic resistance" ~ "Antibiotic resistance", + tolower(trimws(topic)) %in% c("emm types", "emm types") ~ "Emm types", + TRUE ~ topic + ), + time = as.Date(paste0(year, "-12-31")), + geography = "00" + ) + + # --------------------------------------------------------------------------- + # 1. Case rates and death rates (by age, sex, race, and overall) + # --------------------------------------------------------------------------- + rate_topics <- c("Case rates", "Death rates") + + make_measure <- function(df) { + df %>% mutate(measure = if_else(topic == "Case rates", "case_rate", "death_rate")) + } + + # Overall (one row per year/measure) + rates_overall <- data_raw %>% + filter(topic %in% rate_topics, viewby == "Overall") %>% + make_measure() %>% + mutate(age = "Overall", sex = "Overall", race_ethnicity = "Overall") + + # Age-stratified (exclude the Overall row within Age viewby) + age_map <- c( + "<1 year old" = "<1 years", + "1 year old" = "1 year old", + "1 years old" = "1 year old", + "2-4 years old" = "2-4 years old", + "5-17 years old" = "5-17 years old", + "18-34 years old" = "18-34 years old", + "35-49 years old" = "35-49 years old", + "50-64 years old" = "50-64 years old", + "\u226565 years old" = "65+ years olds" + ) + rates_age <- data_raw %>% + filter(topic %in% rate_topics, viewby == "Age", viewby2 %in% names(age_map)) %>% + make_measure() %>% + mutate(age = age_map[viewby2], sex = "Overall", race_ethnicity = "Overall") + + # Sex-stratified (Male/Female only — Overall already covered above) + rates_sex <- data_raw %>% + filter(topic %in% rate_topics, viewby == "Sex", viewby2 %in% c("Male", "Female")) %>% + make_measure() %>% + mutate(age = "Overall", sex = viewby2, race_ethnicity = "Overall") + + # Race-stratified (non-Overall values only) + race_map <- c("Black" = "Black", "White" = "White", "Other races" = "Other") + rates_race <- data_raw %>% + filter(topic %in% rate_topics, viewby == "Race", viewby2 %in% names(race_map)) %>% + make_measure() %>% + mutate(age = "Overall", sex = "Overall", race_ethnicity = race_map[viewby2]) + + data_rates <- bind_rows(rates_overall, rates_age, rates_sex, rates_race) %>% + mutate(measure = if_else(measure == "case_rate", "abcs_gas_rate_cases", "abcs_gas_rate_deaths")) %>% + select(geography, time, age, sex, race_ethnicity, measure, value) + + # --------------------------------------------------------------------------- + # 2. Total case counts and deaths (national aggregate) + # --------------------------------------------------------------------------- + data_counts <- data_raw %>% + filter( + topic == "Number of cases and deaths", + viewby == "ALL" + ) %>% + mutate( + measure = case_when( + viewby2 == "Total cases" ~ "abcs_gas_N_cases", + viewby2 == "Number of deaths" ~ "abcs_gas_N_deaths", + TRUE ~ NA_character_ + ), + age = "Overall", + sex = "Overall", + race_ethnicity = "Overall" + ) %>% + filter(!is.na(measure)) %>% + # Source has duplicate 2023 "Total cases" entries; keep the larger (national estimate) + group_by(geography, time, measure) %>% + slice_max(value, n = 1, with_ties = FALSE) %>% + ungroup() %>% + select(geography, time, age, sex, race_ethnicity, measure, value) + + data_main <- bind_rows(data_rates, data_counts) %>% + tidyr::pivot_wider( + id_cols = c(geography, time, age, sex, race_ethnicity), + names_from = measure, + values_from = value + ) + + vroom::vroom_write(data_main, "standard/data.csv.gz", delim = ",") + + # --------------------------------------------------------------------------- + # 3. Syndromes (percent of cases by clinical presentation) + # --------------------------------------------------------------------------- + syndrome_name_map <- c( + "Cellulitis" = "cellulitis", + "Bacteremia without focus" = "bacteremia_without_focus", + "Pneumonia" = "pneumonia", + "Necrotizing fasciitis" = "necrotizing_fasciitis", + "Streptococcal toxic shock" = "strep_toxic_shock", + "Other" = "other" + ) + + data_syndromes <- data_raw %>% + filter(topic == "Syndromes", viewby %in% names(syndrome_name_map)) %>% + mutate( + measure = paste0("abcs_gas_pct_syndrome_", syndrome_name_map[viewby]) + ) %>% + select(geography, time, measure, value) %>% + tidyr::pivot_wider(names_from = measure, values_from = value) + + vroom::vroom_write(data_syndromes, "standard/data_syndromes.csv.gz", delim = ",") + + # --------------------------------------------------------------------------- + # 4. Antibiotic resistance (percent resistant / number of isolates) + # --------------------------------------------------------------------------- + antibiotics <- c( + "Penicillin", "Erythromycin", "Clindamycin**", + "Cefotaxime", "Tetracycline", "Vancomycin", "Number of isolates" + ) + + data_resistance <- data_raw %>% + filter(topic == "Antibiotic resistance", viewby %in% antibiotics) %>% + mutate( + drug = tolower(sub("\\*\\*$", "", viewby)), + measure = if_else( + viewby == "Number of isolates", + "abcs_gas_n_isolates", + paste0("abcs_gas_pct_resistant_", drug) + ) + ) %>% + select(geography, time, measure, value) %>% + tidyr::pivot_wider(names_from = measure, values_from = value) + + vroom::vroom_write(data_resistance, "standard/data_resistance.csv.gz", delim = ",") + + # --------------------------------------------------------------------------- + # 5. emm types (percent and counts of isolates by emm type) + # --------------------------------------------------------------------------- + data_emm <- data_raw %>% + filter(topic == "Emm types") %>% + mutate( + emm_clean = tolower(gsub("[^a-zA-Z0-9]", "_", viewby)), + measure = case_when( + units == "Percent" ~ paste0("abcs_gas_emm_pct_", emm_clean), + TRUE ~ paste0("abcs_gas_emm_count_", emm_clean) + ) + ) %>% + select(geography, time, measure, value) %>% + tidyr::pivot_wider(names_from = measure, values_from = value) + + vroom::vroom_write(data_emm, "standard/data_emm.csv.gz", delim = ",") + + # --------------------------------------------------------------------------- + # 6. Record processed state + # --------------------------------------------------------------------------- + process$raw_state <- raw_state + dcf::dcf_process_record(updated = process) +} diff --git a/data/abcs_gas/measure_info.json b/data/abcs_gas/measure_info.json new file mode 100644 index 000000000..beef83159 --- /dev/null +++ b/data/abcs_gas/measure_info.json @@ -0,0 +1,141 @@ +{ + "case_rate": { + "id": "case_rate", + "short_name": "Invasive GAS case rate", + "long_name": "Invasive Group A Streptococcus case rate", + "category": "Bacterial diseases", + "short_description": "Incidence rate of invasive Group A Streptococcus disease per 100,000 population", + "long_description": "Annual incidence rate of invasive Group A Streptococcus (iGAS) disease per 100,000 population, from CDC Active Bacterial Core surveillance (ABCs). Rates are available by age group, sex, and race.", + "statement": "In {location}, the invasive GAS case rate was {value} per 100,000 population.", + "measure_type": "Rate", + "unit": "Per 100,000 population", + "time_resolution": "Year", + "sources": [{ "id": "abcs_gas" }], + "citations": [] + }, + "death_rate": { + "id": "death_rate", + "short_name": "Invasive GAS death rate", + "long_name": "Invasive Group A Streptococcus death rate", + "category": "Bacterial diseases", + "short_description": "Mortality rate from invasive Group A Streptococcus disease per 100,000 population", + "long_description": "Annual mortality rate from invasive Group A Streptococcus (iGAS) disease per 100,000 population, from CDC Active Bacterial Core surveillance (ABCs). Rates are available by age group, sex, and race.", + "statement": "In {location}, the invasive GAS death rate was {value} per 100,000 population.", + "measure_type": "Rate", + "unit": "Per 100,000 population", + "time_resolution": "Year", + "sources": [{ "id": "abcs_gas" }], + "citations": [] + }, + "n_cases": { + "id": "n_cases", + "short_name": "Invasive GAS case count", + "long_name": "Number of invasive Group A Streptococcus cases", + "category": "Bacterial diseases", + "short_description": "Total number of invasive Group A Streptococcus cases in the ABCs catchment area", + "long_description": "Annual count of invasive Group A Streptococcus (iGAS) disease cases in the CDC ABCs surveillance catchment area.", + "statement": "In {location}, {value} invasive GAS cases were reported.", + "measure_type": "Count", + "unit": "Count", + "time_resolution": "Year", + "sources": [{ "id": "abcs_gas" }], + "citations": [] + }, + "n_deaths": { + "id": "n_deaths", + "short_name": "Invasive GAS death count", + "long_name": "Number of deaths from invasive Group A Streptococcus", + "category": "Bacterial diseases", + "short_description": "Total number of deaths from invasive Group A Streptococcus in the ABCs catchment area", + "long_description": "Annual count of deaths from invasive Group A Streptococcus (iGAS) disease in the CDC ABCs surveillance catchment area.", + "statement": "In {location}, {value} deaths from invasive GAS were reported.", + "measure_type": "Count", + "unit": "Count", + "time_resolution": "Year", + "sources": [{ "id": "abcs_gas" }], + "citations": [] + }, + "n_survivals": { + "id": "n_survivals", + "short_name": "Invasive GAS survival count", + "long_name": "Number of survivors of invasive Group A Streptococcus", + "category": "Bacterial diseases", + "short_description": "Total number of survivors of invasive Group A Streptococcus in the ABCs catchment area", + "long_description": "Annual count of survivors of invasive Group A Streptococcus (iGAS) disease in the CDC ABCs surveillance catchment area.", + "statement": "In {location}, {value} people survived invasive GAS disease.", + "measure_type": "Count", + "unit": "Count", + "time_resolution": "Year", + "sources": [{ "id": "abcs_gas" }], + "citations": [] + }, + "syndrome": { + "id": "syndrome", + "short_name": "Clinical syndrome", + "long_name": "Clinical syndrome of invasive GAS case", + "category": "Bacterial diseases", + "short_description": "Percent of invasive GAS cases by clinical syndrome (cellulitis, STSS, necrotizing fasciitis, etc.)", + "long_description": "Annual distribution of clinical syndromes among invasive Group A Streptococcus cases. Syndromes include cellulitis, bacteremia without focus, pneumonia, necrotizing fasciitis, streptococcal toxic shock syndrome (STSS), and other.", + "statement": "", + "measure_type": "Percent", + "unit": "Percent", + "time_resolution": "Year", + "sources": [{ "id": "abcs_gas" }], + "citations": [] + }, + "pct_resistant": { + "id": "pct_resistant", + "short_name": "Antibiotic resistance (%)", + "long_name": "Percent of GAS isolates resistant to antibiotic", + "category": "Bacterial diseases", + "short_description": "Percent of invasive GAS isolates showing resistance to a given antibiotic", + "long_description": "Annual percent of invasive Group A Streptococcus isolates demonstrating non-susceptibility to antibiotics including penicillin, erythromycin, clindamycin, cefotaxime, tetracycline, and vancomycin. Data from CDC ABCs.", + "statement": "", + "measure_type": "Percent", + "unit": "Percent", + "time_resolution": "Year", + "sources": [{ "id": "abcs_gas" }], + "citations": [] + }, + "n_isolates": { + "id": "n_isolates", + "short_name": "Number of GAS isolates tested", + "long_name": "Number of invasive GAS isolates tested for antibiotic susceptibility", + "category": "Bacterial diseases", + "short_description": "Total number of invasive GAS isolates tested for antibiotic susceptibility", + "long_description": "Annual count of invasive Group A Streptococcus isolates submitted for antibiotic susceptibility testing in the CDC ABCs catchment area.", + "statement": "", + "measure_type": "Count", + "unit": "Count", + "time_resolution": "Year", + "sources": [{ "id": "abcs_gas" }], + "citations": [] + }, + "emm_type": { + "id": "emm_type", + "short_name": "emm type", + "long_name": "GAS emm type", + "category": "Bacterial diseases", + "short_description": "Distribution of GAS emm types among invasive isolates", + "long_description": "Annual distribution of emm types (surface protein gene sequence types) among invasive Group A Streptococcus isolates from the CDC ABCs catchment area. emm typing is used to track GAS strain diversity and vaccine coverage.", + "statement": "", + "measure_type": "Percent", + "unit": "Percent", + "time_resolution": "Year", + "sources": [{ "id": "abcs_gas" }], + "citations": [] + }, + "_sources": { + "abcs_gas": { + "name": "Active Bacterial Core surveillance (ABCs) - Group A Streptococcus", + "url": "https://data.cdc.gov/Public-Health-Surveillance/Active-Bacterial-Core-surveillance-ABCs-Group-A-St/9y49-tura/about_data", + "organization": "Centers for Disease Control and Prevention", + "organization_url": "https://www.cdc.gov", + "location": "Active Bacterial Core surveillance (ABCs) Group A Streptococcus data on data.cdc.gov", + "location_url": "https://data.cdc.gov/resource/9y49-tura/", + "date_accessed": 2025, + "description": "CDC monitors invasive bacterial infections through Active Bacterial Core surveillance (ABCs), a population-based surveillance program for invasive bacterial diseases in selected geographic areas of the United States. This dataset reports annual data on invasive Group A Streptococcus (iGAS) disease from 1997 onwards, including case and death rates by age group, sex, and race; clinical syndrome distribution (cellulitis, bacteremia without focus, pneumonia, necrotizing fasciitis, streptococcal toxic shock syndrome); antibiotic resistance patterns; and emm type distribution among isolates. ABCs catchment areas include California, Colorado, Connecticut, Georgia, Maryland, Minnesota, New York, Oregon, and Tennessee, representing approximately 10% of the US population. Incidence rates are calculated using U.S. Census Bureau population estimates for the respective catchment areas.", + "restrictions": "Public domain. CDC data is generally not subject to copyright restrictions." + } + } +} diff --git a/data/abcs_gas/process.json b/data/abcs_gas/process.json new file mode 100644 index 000000000..7b84fa788 --- /dev/null +++ b/data/abcs_gas/process.json @@ -0,0 +1,33 @@ +{ + "name": "abcs_gas", + "type": "source", + "scripts": [ + { + "path": "ingest.R", + "manual": false, + "frequency": 0, + "last_run": "", + "run_time": "", + "last_status": { + "log": "", + "success": true + } + } + ], + "checked": "2026-08-05 15:59:49", + "check_results": { + "data/abcs_gas/standard/data.csv.gz": { + "measures": ["missing_info: age", "missing_info: sex", "missing_info: race_ethnicity", "missing_info: abcs_gas_rate_cases", "missing_info: abcs_gas_rate_deaths", "missing_info: abcs_gas_N_cases", "missing_info: abcs_gas_N_deaths"] + }, + "data/abcs_gas/standard/data_emm.csv.gz": { + "measures": ["missing_info: abcs_gas_emm_count_number_of_isolates", "missing_info: abcs_gas_emm_pct_other", "missing_info: abcs_gas_emm_pct_emm_1", "missing_info: abcs_gas_emm_pct_emm_11", "missing_info: abcs_gas_emm_pct_emm_12", "missing_info: abcs_gas_emm_pct_emm_28", "missing_info: abcs_gas_emm_pct_emm_43", "missing_info: abcs_gas_emm_pct_emm_59", "missing_info: abcs_gas_emm_pct_emm_77", "missing_info: abcs_gas_emm_pct_emm_82", "missing_info: abcs_gas_emm_pct_emm_83", "missing_info: abcs_gas_emm_pct_emm_89", "missing_info: abcs_gas_emm_pct_emm_92", "missing_info: abcs_gas_emm_pct_emm_49", "missing_info: abcs_gas_emm_pct_emm_81", "missing_info: abcs_gas_emm_pct_emm_60", "missing_info: abcs_gas_emm_pct_emm_91"] + }, + "data/abcs_gas/standard/data_resistance.csv.gz": { + "measures": ["missing_info: abcs_gas_pct_resistant_cefotaxime", "missing_info: abcs_gas_pct_resistant_clindamycin", "missing_info: abcs_gas_pct_resistant_erythromycin", "missing_info: abcs_gas_pct_resistant_penicillin", "missing_info: abcs_gas_pct_resistant_tetracycline", "missing_info: abcs_gas_pct_resistant_vancomycin", "missing_info: abcs_gas_n_isolates"] + }, + "data/abcs_gas/standard/data_syndromes.csv.gz": { + "measures": ["missing_info: abcs_gas_pct_syndrome_cellulitis", "missing_info: abcs_gas_pct_syndrome_bacteremia_without_focus", "missing_info: abcs_gas_pct_syndrome_pneumonia", "missing_info: abcs_gas_pct_syndrome_necrotizing_fasciitis", "missing_info: abcs_gas_pct_syndrome_strep_toxic_shock"] + } + }, + "raw_state": 1747769158 +} diff --git a/data/abcs_gas/raw/9y49-tura.csv.xz b/data/abcs_gas/raw/9y49-tura.csv.xz new file mode 100644 index 000000000..0e186d938 Binary files /dev/null and b/data/abcs_gas/raw/9y49-tura.csv.xz differ diff --git a/data/abcs_gas/raw/9y49-tura.json b/data/abcs_gas/raw/9y49-tura.json new file mode 100644 index 000000000..cb9ba658b --- /dev/null +++ b/data/abcs_gas/raw/9y49-tura.json @@ -0,0 +1,515 @@ +{ + "id" : "9y49-tura", + "name" : "Active Bacterial Core surveillance (ABCs) Group A Streptococcus", + "assetType" : "dataset", + "attribution" : "CDC", + "attributionLink" : "https://www.cdc.gov/abcs/bact-facts/data-dashboard.html", + "averageRating" : 0, + "category" : "Public Health Surveillance", + "createdAt" : 1621531278, + "description" : "ABCs is an ongoing surveillance program that began in 1997. 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Interactive may differ from other ABCs publications since different datasets or methods may be used. **Small numbers for some topics or filters may make year to year changes difficult to interpret. ***Since each infection may have unique characteristics, the information available to display differs by individual bacterium." + }, + "Common Core" : { + "Contact Email" : "abcs@cdc.gov", + "Contact Name" : "Active Bacterial Core surveillance", + "Program Code" : "009:020", + "Bureau Code" : "009:20", + "Public Access Level" : "public" + } + }, + "availableDisplayTypes" : [ "table", "fatrow", "page" ] + }, + "owner" : { + "id" : "wnru-jmaq", + "displayName" : "Active Bacterial Core Surveillance", + "screenName" : "Active Bacterial Core Surveillance", + "type" : "interactive", + "flags" : [ "acceptedEula", "mayBeStoriesCoOwner" ] + }, + "query" : { }, + "rights" : [ "read" ], + "tableAuthor" : { + "id" : "wnru-jmaq", + "displayName" : "Active Bacterial Core Surveillance", + "screenName" : "Active Bacterial Core Surveillance", + "type" : "interactive", + "flags" : [ "acceptedEula", "mayBeStoriesCoOwner" ] + }, + "tags" : [ "bactfacts", "abcs" ], + "flags" : [ "default", "ownerMayBeContacted", "restorable", "restorePossibleForType" ] +} diff --git a/data/abcs_gas/standard/data.csv.gz b/data/abcs_gas/standard/data.csv.gz new file mode 100644 index 000000000..62f1ecb7a Binary files /dev/null and b/data/abcs_gas/standard/data.csv.gz differ diff --git a/data/abcs_gas/standard/data_emm.csv.gz b/data/abcs_gas/standard/data_emm.csv.gz new file mode 100644 index 000000000..f3bac46d7 Binary files /dev/null and b/data/abcs_gas/standard/data_emm.csv.gz differ diff --git a/data/abcs_gas/standard/data_resistance.csv.gz b/data/abcs_gas/standard/data_resistance.csv.gz new file mode 100644 index 000000000..279b7640c Binary files /dev/null and b/data/abcs_gas/standard/data_resistance.csv.gz differ diff --git a/data/abcs_gas/standard/data_syndromes.csv.gz b/data/abcs_gas/standard/data_syndromes.csv.gz new file mode 100644 index 000000000..b8289b463 Binary files /dev/null and b/data/abcs_gas/standard/data_syndromes.csv.gz differ diff --git a/data/abcs_gas/standard/datapackage.json b/data/abcs_gas/standard/datapackage.json new file mode 100644 index 000000000..5d03651eb --- /dev/null +++ b/data/abcs_gas/standard/datapackage.json @@ -0,0 +1,11 @@ +{ + "name": "abcs_gas", + "title": "Abcs Gas", + "licence": { + "url": "http://opendatacommons.org/licenses/pddl", + "name": "Open Data Commons Public Domain", + "version": "1.0", + "id": "odc-pddl" + }, + "resources": [] +} diff --git a/data/bundle_gas/.gitignore b/data/bundle_gas/.gitignore new file mode 100644 index 000000000..3eb01b5c6 --- /dev/null +++ b/data/bundle_gas/.gitignore @@ -0,0 +1,7 @@ +*.Rproj +.Rproj.user +*.Rprofile +*.Rhistory +*.Rdata +.DS_Store +renv diff --git a/data/bundle_gas/README.md b/data/bundle_gas/README.md new file mode 100644 index 000000000..eb90f7b24 --- /dev/null +++ b/data/bundle_gas/README.md @@ -0,0 +1,57 @@ +# bundle_gas + +Group A Streptococcus (GAS) surveillance, combining three sources at three very +different grains. Built by `build.R` into six long-format parquets under `dist/`. + +| Parquet | Source | Grain | Measures | +|---|---|---|---| +| `epic_gas.parquet` | `epic_gas` | State + national, quarterly, by age | `n_strep_throat`, `pct_strep_throat`, `n_patients` | +| `nnds_stss.parquet` | `nnds` | State + national, weekly (MMWR) | `stss_cases_weekly`, `stss_cases_cumulative` | +| `abcs_gas.parquet` | `abcs_gas` | National, annual, by age/sex/race | `rate_cases`, `rate_deaths`, `N_cases`, `N_deaths` | +| `abcs_gas_syndromes.parquet` | `abcs_gas` | National, annual | `pct_syndrome_*` (5 syndromes) | +| `abcs_gas_resistance.parquet` | `abcs_gas` | National, annual | `pct_resistant_*` (6 antibiotics), `n_isolates` | +| `abcs_gas_emm.parquet` | `abcs_gas` | National, annual | `emm_pct_*` (16 types + other), isolate count | + +All six share the bundle conventions: `geography` holds **state names** (or +`"United States"`), `time` is ISO `YYYY-mm-dd` period-end, and `value` is the +plotting column, keyed by a `measure` identifier column. + +## Notes for anyone reading these files + +- **`measure` mixes units within `value`.** In `epic_gas.parquet`, `n_*` measures + are counts while `pct_strep_throat` is a percent; the ABCs files mix rates, + percents, and isolate counts. Always filter or facet by `measure` before + plotting. +- **NNDSS is published cumulatively.** The raw + `streptococcal_toxic_shock_syndrome` column is a *year-to-date running total* + that resets each MMWR year (national 2024 runs 5 → 647 across weeks 1–52). + `build.R` de-accumulates it into `stss_cases_weekly`, which is the series to + plot; `stss_cases_cumulative` retains the published form. The two are not + additive. NNDSS sometimes revises earlier weeks downward, so a small number of + weekly increments are negative (27 of 12,376 at the current build); these are + left as reported rather than clamped, and `build.R` logs the count. +- **Aggregate levels overlap.** `epic_gas.parquet` carries an `age` level of + `"Total"`, and `abcs_gas.parquet` carries `"Overall"` levels for `age`, `sex`, + and `race_ethnicity`. Exclude these before summing across a stratification. +- **Geographic coverage is uneven.** Epic and NNDSS cover states plus a national + total; the ABCs files are national only (a ~35 million person catchment area, + not the whole US). Territories and non-state NNDSS jurisdictions (e.g. New York + City) are dropped. +- **Two different strep toxic shock series exist.** + `nnds_stss.parquet` gives national/state case *counts*, while + `abcs_gas_syndromes.parquet`'s `pct_syndrome_strep_toxic_shock` gives the + *percent* of invasive GAS cases in the ABCs catchment presenting as STSS. They + are not comparable directly. +- **Epic denominators are all encounters, not ED visits.** `n_patients` counts + patients with any encounter, so `pct_strep_throat` is not an ED visit share. +- **Time spans differ**: Epic 2017-Q1 → 2025-Q4, NNDSS 2022 → present, ABCs + 1997 → 2023. Any cross-source comparison is limited to the overlap. + +This is a Data Collection Framework data bundle project, initialized with +`dcf::dcf_add_bundle`. + +You can use the `dcf` package to rebuild the bundle: + +```R +dcf::dcf_process("bundle_gas") +``` diff --git a/data/bundle_gas/build.R b/data/bundle_gas/build.R new file mode 100644 index 000000000..194bff079 --- /dev/null +++ b/data/bundle_gas/build.R @@ -0,0 +1,169 @@ +# ============================================================================= +# Bundle: Group A Streptococcus (GAS) +# Combines: epic_gas (Epic Cosmos strep throat patients, quarterly, by state/age) +# nnds (NNDSS streptococcal toxic shock syndrome, weekly, by state) +# abcs_gas (CDC ABCs Group A Streptococcus, annual, national) +# Outputs (all long format, `value` is the plotting column, `geography` holds +# state names / "United States"): +# 1. epic_gas.parquet - strep throat counts, percent, denominator +# 2. nnds_stss.parquet - STSS cases, weekly-incident and cumulative +# 3. abcs_gas.parquet - GAS case/death rates and counts +# 4. abcs_gas_syndromes.parquet - clinical syndrome distribution +# 5. abcs_gas_resistance.parquet - antibiotic resistance +# 6. abcs_gas_emm.parquet - emm type distribution +# ============================================================================= + +library(dplyr) +library(tidyr) +library(arrow) + +process <- dcf::dcf_process_record() + +dir.create("dist", showWarnings = FALSE) + +# ----------------------------------------------------------------------------- +# 0. FIPS -> state name lookup (dist files use names, not FIPS, for states) +# ----------------------------------------------------------------------------- +state_name_lookup <- vroom::vroom( + "../../resources/all_fips.csv.gz", + show_col_types = FALSE +) %>% + filter(nchar(geography) == 2) %>% + select(fips = geography, geography_name) + +# Keep only the 50 states, DC, and the national total +keep_geographies <- c(state.name, "District of Columbia", "United States") + +fips_to_name <- function(df) { + df %>% + rename(fips = geography) %>% + left_join(state_name_lookup, by = "fips") %>% + mutate(geography = if_else(fips == "00", "United States", geography_name)) %>% + filter(geography %in% keep_geographies) %>% + select(-fips, -geography_name) %>% + relocate(geography) +} + +# ----------------------------------------------------------------------------- +# 1. Epic Cosmos strep throat -> long +# Two suppression flags upstream: the numerator flag covers both the count +# and the percent (the percent is derived from that same cell), the +# denominator flag covers the patient total. Map each measure to its own. +# ----------------------------------------------------------------------------- +epic_gas <- vroom::vroom( + "../epic_gas/standard/data.csv.gz", + show_col_types = FALSE, + col_types = vroom::cols(geography = "c", time = "D", age = "c") +) %>% + fips_to_name() %>% + select( + geography, time, age, + n_strep_throat = epic_n_strep_throat, + pct_strep_throat = epic_pct_strep_throat, + n_patients = epic_n_patients, + .numerator_flag = epic_strep_throat_suppressed_flag, + .denominator_flag = epic_n_patients_suppressed_flag + ) %>% + pivot_longer( + c(n_strep_throat, pct_strep_throat, n_patients), + names_to = "measure", + values_to = "value" + ) %>% + mutate( + suppressed = if_else(measure == "n_patients", .denominator_flag, .numerator_flag) + ) %>% + select(geography, time, age, measure, value, suppressed) %>% + arrange(geography, time, age, measure) + +arrow::write_parquet(epic_gas, "dist/epic_gas.parquet") + +# ----------------------------------------------------------------------------- +# 2. NNDSS streptococcal toxic shock syndrome -> long +# NNDSS reports counts cumulatively within each MMWR year (national 2024 +# ramps 5 -> 647 across weeks 1-52), so the series must be de-accumulated +# before it can be plotted as weekly incidence. Both forms are emitted. +# ----------------------------------------------------------------------------- +nnds_stss <- vroom::vroom( + "../nnds/standard/data.csv.gz", + show_col_types = FALSE, + col_select = c(time, mmwr_year, mmwr_week, geography, + streptococcal_toxic_shock_syndrome), + col_types = vroom::cols(geography = "c", time = "D") +) %>% + rename(stss_cases_cumulative = streptococcal_toxic_shock_syndrome) %>% + filter(!is.na(geography)) %>% + fips_to_name() %>% + arrange(geography, mmwr_year, mmwr_week) %>% + group_by(geography, mmwr_year) %>% + # cumulative counts reset each MMWR year, so the year's first week is itself + # the increment (default = 0) + mutate( + stss_cases_weekly = stss_cases_cumulative - + lag(stss_cases_cumulative, default = 0) + ) %>% + ungroup() + +# NNDSS revises prior weeks downward on occasion, which shows up as a negative +# increment. Report rather than silently clamp. +n_negative <- sum(nnds_stss$stss_cases_weekly < 0, na.rm = TRUE) +if (n_negative > 0) { + message( + "NNDSS: ", n_negative, " of ", nrow(nnds_stss), + " weekly increments are negative (downward revisions to the cumulative ", + "count); left as-is." + ) +} + +nnds_stss <- nnds_stss %>% + select(geography, time, stss_cases_weekly, stss_cases_cumulative) %>% + pivot_longer( + c(stss_cases_weekly, stss_cases_cumulative), + names_to = "measure", + values_to = "value" + ) %>% + filter(!is.na(value)) %>% + arrange(geography, time, measure) + +arrow::write_parquet(nnds_stss, "dist/nnds_stss.parquet") + +# ----------------------------------------------------------------------------- +# 3. ABCs Group A Streptococcus -> long (one parquet per upstream file) +# All four are national-only (geography "00") and annual (YYYY-12-31). +# Measure names drop the redundant `abcs_gas_` source prefix. +# ----------------------------------------------------------------------------- +melt_abcs <- function(file, id_cols) { + vroom::vroom( + file.path("../abcs_gas/standard", file), + show_col_types = FALSE, + col_types = vroom::cols(geography = "c", time = "D") + ) %>% + fips_to_name() %>% + pivot_longer( + -all_of(id_cols), + names_to = "measure", + values_to = "value" + ) %>% + mutate(measure = sub("^abcs_gas_", "", measure)) %>% + filter(!is.na(value)) %>% + arrange(across(all_of(c(id_cols, "measure")))) +} + +arrow::write_parquet( + melt_abcs("data.csv.gz", c("geography", "time", "age", "sex", "race_ethnicity")), + "dist/abcs_gas.parquet" +) + +arrow::write_parquet( + melt_abcs("data_syndromes.csv.gz", c("geography", "time")), + "dist/abcs_gas_syndromes.parquet" +) + +arrow::write_parquet( + melt_abcs("data_resistance.csv.gz", c("geography", "time")), + "dist/abcs_gas_resistance.parquet" +) + +arrow::write_parquet( + melt_abcs("data_emm.csv.gz", c("geography", "time")), + "dist/abcs_gas_emm.parquet" +) diff --git a/data/bundle_gas/dist/abcs_gas.parquet b/data/bundle_gas/dist/abcs_gas.parquet new file mode 100644 index 000000000..f2cfc1d05 Binary files /dev/null and b/data/bundle_gas/dist/abcs_gas.parquet differ diff --git a/data/bundle_gas/dist/abcs_gas_emm.parquet b/data/bundle_gas/dist/abcs_gas_emm.parquet new file mode 100644 index 000000000..f8157ca06 Binary files /dev/null and b/data/bundle_gas/dist/abcs_gas_emm.parquet differ diff --git a/data/bundle_gas/dist/abcs_gas_resistance.parquet b/data/bundle_gas/dist/abcs_gas_resistance.parquet new file mode 100644 index 000000000..35d161519 Binary files /dev/null and b/data/bundle_gas/dist/abcs_gas_resistance.parquet differ diff --git a/data/bundle_gas/dist/abcs_gas_syndromes.parquet b/data/bundle_gas/dist/abcs_gas_syndromes.parquet new file mode 100644 index 000000000..f5983c4f7 Binary files /dev/null and b/data/bundle_gas/dist/abcs_gas_syndromes.parquet differ diff --git a/data/bundle_gas/dist/datapackage.json b/data/bundle_gas/dist/datapackage.json new file mode 100644 index 000000000..9a0ae6799 --- /dev/null +++ b/data/bundle_gas/dist/datapackage.json @@ -0,0 +1,1042 @@ +{ + "name": "bundle_gas", + "title": "Bundle Gas", + "licence": { + "url": "http://opendatacommons.org/licenses/pddl", + "name": "Open Data Commons Public Domain", + "version": "1.0", + "id": "odc-pddl" + }, + "resources": [ + { + "bytes": 4458, + "encoding": "ISO-8859-1", + "md5": "8f1bd8f1b36a7cb3bc3e730ce7f7da2f", + "format": "parquet", + "name": "abcs_gas", + "filename": "abcs_gas.parquet", + "versions": {}, + "source": [], + "data_format": "wide", + "ids": [ + { + "variable": "geography" + } + ], + "id_length": 13, + "time": "time", + "profile": "data-resource", + "created": "2026-08-05 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"2026-04-18": 104, + "2026-04-25": 104, + "2026-05-02": 104, + "2026-05-09": 104, + "2026-05-16": 104, + "2026-05-23": 104, + "2026-05-30": 104, + "2026-06-06": 104, + "2026-06-13": 104, + "2026-06-20": 104, + "2026-06-27": 104, + "2026-07-04": 104, + "2026-07-11": 104, + "2026-07-18": 104, + "2026-07-25": 104 + } + }, + { + "name": "measure", + "duplicates": 24750, + "info": [], + "time_range": [0, 237], + "type": "string", + "missing": 0, + "table": { + "stss_cases_cumulative": 12376, + "stss_cases_weekly": 12376 + } + }, + { + "name": "value", + "duplicates": 24509, + "info": [], + "time_range": [0, 237], + "type": "integer", + "missing": 0, + "mean": 4.492889, + "sd": 29.227077, + "min": -3, + "max": 647 + } + ] + }, + "sha512": "0e0bc05f39e5dbc7dfa6844e8d34e7575cfd46b0f7761f2ce036ee7883f4767a68d1d2917cdfdb69261e1adf36708739e91910484045506336d4bf592ed12b9a" + } + ], + "measure_info": [] +} diff --git a/data/bundle_gas/dist/epic_gas.parquet b/data/bundle_gas/dist/epic_gas.parquet new file mode 100644 index 000000000..6da845c21 Binary files /dev/null and b/data/bundle_gas/dist/epic_gas.parquet differ diff --git a/data/bundle_gas/dist/nnds_stss.parquet b/data/bundle_gas/dist/nnds_stss.parquet new file mode 100644 index 000000000..f42d55853 Binary files /dev/null and b/data/bundle_gas/dist/nnds_stss.parquet differ diff --git a/data/bundle_gas/measure_info.json b/data/bundle_gas/measure_info.json new file mode 100644 index 000000000..3f404e5f2 --- /dev/null +++ b/data/bundle_gas/measure_info.json @@ -0,0 +1,235 @@ +{ + "{category}geography": { + "short_name": "Geography", + "long_name": "Geography (state name or national total)", + "short_description": "State name, or \"United States\" for the national total.", + "long_description": "Geographic identifier. Unlike the standard source files, bundle dist files use state *names* rather than FIPS codes; the national total is the literal string \"United States\". Only the 50 states, the District of Columbia, and the national total are retained - territories and non-state NNDSS reporting jurisdictions (e.g. New York City) are dropped by build.R.", + "measure_type": "identifier", + "unit": "state name", + "categories": { + "bundle_gas/dist/epic_gas.parquet|": {}, + "bundle_gas/dist/nnds_stss.parquet|": {}, + "bundle_gas/dist/abcs_gas.parquet|": {}, + "bundle_gas/dist/abcs_gas_syndromes.parquet|": {}, + "bundle_gas/dist/abcs_gas_resistance.parquet|": {}, + "bundle_gas/dist/abcs_gas_emm.parquet|": {} + } + }, + + "{category}time": { + "short_name": "Time", + "long_name": "Time period end date", + "short_description": "Period end date in YYYY-mm-dd (ISO 8601) format.", + "long_description": "End date of the reporting period, in YYYY-mm-dd format. The resolution differs by file: Epic Cosmos is quarterly (last day of the calendar quarter), NNDSS is weekly (MMWR week ending Saturday), and the ABCs files are annual (YYYY-12-31).", + "measure_type": "date", + "unit": "date", + "categories": { + "bundle_gas/dist/epic_gas.parquet|": {}, + "bundle_gas/dist/nnds_stss.parquet|": {}, + "bundle_gas/dist/abcs_gas.parquet|": {}, + "bundle_gas/dist/abcs_gas_syndromes.parquet|": {}, + "bundle_gas/dist/abcs_gas_resistance.parquet|": {}, + "bundle_gas/dist/abcs_gas_emm.parquet|": {} + } + }, + + "bundle_gas/dist/epic_gas.parquet|age": { + "short_name": "Age Group", + "long_name": "Age group at encounter", + "short_description": "Epic Cosmos age band; \"Total\" is the all-ages aggregate.", + "long_description": "Age at encounter, as banded by Epic Cosmos SlicerDicer. Levels are \"<1 Years\", \"1-4 Years\", \"5-17 Years\", \"18-49 Years\", \"50-64 Years\", \"65+ Years\", and \"Total\". \"Total\" is an all-ages aggregate that overlaps the individual bands, so it must be excluded when summing across ages.", + "measure_type": "category", + "unit": "" + }, + + "bundle_gas/dist/epic_gas.parquet|measure": { + "short_name": "Measure", + "levels": { + "n_strep_throat": { "source_id": "epic_n_strep_throat" }, + "pct_strep_throat": { "source_id": "epic_pct_strep_throat" }, + "n_patients": { "source_id": "epic_n_patients" } + } + }, + + "bundle_gas/dist/epic_gas.parquet|value": { + "short_name": "Value", + "long_name": "Epic Cosmos strep throat measure value", + "short_description": "Value of the measure named in the `measure` column; unit depends on that measure.", + "long_description": "Value of the measure named in the `measure` column. The unit depends on the measure: `n_strep_throat` and `n_patients` are patient counts, while `pct_strep_throat` is a percentage (0-100) computed as n_strep_throat / n_patients * 100. Because units are mixed within this column, always facet or filter by `measure` before plotting.", + "measure_type": "Mixed", + "unit": "patients or percent", + "time_resolution": "Quarter", + "sources": [{ "id": "epic_cosmos" }] + }, + + "bundle_gas/dist/epic_gas.parquet|suppressed": { + "short_name": "Suppressed", + "long_name": "Suppression flag for this measure value", + "short_description": "1 if Epic suppressed the underlying cell and the value was imputed as 5; 0 otherwise.", + "long_description": "1 when Epic Cosmos withheld the underlying cell (a count of 10 or fewer) and the value was imputed as 5; 0 otherwise. The flag is measure-specific: for `n_strep_throat` and `pct_strep_throat` it reflects suppression of the strep throat numerator, and for `n_patients` it reflects suppression of the patient-total denominator. The flag is computed upstream before imputation, so it records what Epic withheld rather than what the ingest wrote.", + "measure_type": "Binary", + "unit": "0/1", + "time_resolution": "Quarter", + "sources": [{ "id": "epic_cosmos" }] + }, + + "bundle_gas/dist/nnds_stss.parquet|measure": { + "short_name": "Measure", + "levels": { + "stss_cases_weekly": { + "short_name": "Strep TSS cases (weekly)", + "long_name": "Weekly incident cases of streptococcal toxic shock syndrome", + "short_description": "Newly reported STSS cases in the MMWR week.", + "long_description": "Incident cases of streptococcal toxic shock syndrome (STSS) newly reported in the MMWR week, derived by build.R as the week-over-week difference in the cumulative year-to-date count within each geography and MMWR year. This is the series to use for plotting trends. NNDSS occasionally revises earlier weeks downward, which produces a small number of negative increments (27 of 12,376 as of the current build); these are left as reported rather than clamped, and build.R logs the count.", + "measure_type": "Count", + "unit": "Cases", + "time_resolution": "Week", + "sources": [{ "id": "nnds" }] + }, + "stss_cases_cumulative": { "source_id": "streptococcal_toxic_shock_syndrome" } + } + }, + + "bundle_gas/dist/nnds_stss.parquet|value": { + "short_name": "Value", + "long_name": "Streptococcal toxic shock syndrome case count", + "short_description": "STSS case count; weekly-incident or cumulative year-to-date per the `measure` column.", + "long_description": "Reported case count of streptococcal toxic shock syndrome (STSS), a life-threatening condition caused by group A Streptococcus. The `measure` column distinguishes the weekly-incident series (`stss_cases_weekly`) from the cumulative year-to-date series as published by NNDSS (`stss_cases_cumulative`). The two are not additive - do not sum across measures.", + "measure_type": "Count", + "unit": "Cases", + "time_resolution": "Week", + "sources": [{ "id": "nnds" }] + }, + + "bundle_gas/dist/abcs_gas.parquet|measure": { + "short_name": "Measure", + "levels": { + "rate_cases": { "source_id": "case_rate" }, + "rate_deaths": { "source_id": "death_rate" }, + "N_cases": { "source_id": "n_cases" }, + "N_deaths": { "source_id": "n_deaths" } + } + }, + + "bundle_gas/dist/abcs_gas.parquet|value": { + "short_name": "Value", + "long_name": "ABCs invasive Group A Streptococcus measure value", + "short_description": "Value of the measure named in the `measure` column; rate per 100,000 or case/death count.", + "long_description": "Value of the measure named in the `measure` column, from CDC's Active Bacterial Core surveillance (ABCs) for invasive Group A Streptococcus. `rate_cases` and `rate_deaths` are incidence rates per 100,000 population; `N_cases` and `N_deaths` are national estimated counts. Units are mixed within this column, so filter by `measure` before plotting. Values are national only and are stratified by age, sex, and race/ethnicity, each of which carries an \"Overall\" level that must not be summed with the specific levels.", + "measure_type": "Mixed", + "unit": "cases per 100,000 or count", + "time_resolution": "Year", + "sources": [{ "id": "abcs_gas" }] + }, + + "bundle_gas/dist/abcs_gas_syndromes.parquet|measure": { + "short_name": "Clinical syndrome", + "levels": { + "pct_syndrome_cellulitis": { "source_id": "syndrome" }, + "pct_syndrome_bacteremia_without_focus": { "source_id": "syndrome" }, + "pct_syndrome_pneumonia": { "source_id": "syndrome" }, + "pct_syndrome_necrotizing_fasciitis": { "source_id": "syndrome" }, + "pct_syndrome_strep_toxic_shock": { "source_id": "syndrome" } + } + }, + + "bundle_gas/dist/abcs_gas_syndromes.parquet|value": { + "short_name": "Percent of cases", + "long_name": "Percent of invasive GAS cases presenting with the clinical syndrome", + "short_description": "Percent of invasive GAS cases presenting with the syndrome named in `measure`.", + "long_description": "Annual percent of invasive Group A Streptococcus cases in the CDC ABCs catchment area presenting with the clinical syndrome named in the `measure` column (cellulitis, bacteremia without focus, pneumonia, necrotizing fasciitis, or streptococcal toxic shock syndrome). Syndromes are not mutually exclusive and do not sum to 100 percent. Note that `pct_syndrome_strep_toxic_shock` measures the same condition as the NNDSS series in nnds_stss.parquet, but as a percentage of ABCs surveillance-area cases rather than a national case count.", + "measure_type": "Percent", + "unit": "Percent", + "time_resolution": "Year", + "sources": [{ "id": "abcs_gas" }] + }, + + "bundle_gas/dist/abcs_gas_resistance.parquet|measure": { + "short_name": "Resistance measure", + "levels": { + "pct_resistant_penicillin": { "source_id": "pct_resistant" }, + "pct_resistant_erythromycin": { "source_id": "pct_resistant" }, + "pct_resistant_clindamycin": { "source_id": "pct_resistant" }, + "pct_resistant_cefotaxime": { "source_id": "pct_resistant" }, + "pct_resistant_tetracycline": { "source_id": "pct_resistant" }, + "pct_resistant_vancomycin": { "source_id": "pct_resistant" }, + "n_isolates": { "source_id": "n_isolates" } + } + }, + + "bundle_gas/dist/abcs_gas_resistance.parquet|value": { + "short_name": "Value", + "long_name": "Antibiotic resistance percent, or isolate count", + "short_description": "Percent of invasive GAS isolates non-susceptible to the antibiotic named in `measure`; or the isolate count.", + "long_description": "For the `pct_resistant_*` measures, the annual percent of invasive Group A Streptococcus isolates demonstrating non-susceptibility to the named antibiotic. For `n_isolates`, the number of isolates tested (the denominator), which is a count rather than a percent. Filter by `measure` before plotting, since units are mixed.", + "measure_type": "Mixed", + "unit": "percent or count", + "time_resolution": "Year", + "sources": [{ "id": "abcs_gas" }] + }, + + "bundle_gas/dist/abcs_gas_emm.parquet|measure": { + "short_name": "emm type measure", + "levels": { + "emm_pct_emm_1": { "source_id": "emm_type" }, + "emm_pct_emm_11": { "source_id": "emm_type" }, + "emm_pct_emm_12": { "source_id": "emm_type" }, + "emm_pct_emm_28": { "source_id": "emm_type" }, + "emm_pct_emm_43": { "source_id": "emm_type" }, + "emm_pct_emm_49": { "source_id": "emm_type" }, + "emm_pct_emm_59": { "source_id": "emm_type" }, + "emm_pct_emm_60": { "source_id": "emm_type" }, + "emm_pct_emm_77": { "source_id": "emm_type" }, + "emm_pct_emm_81": { "source_id": "emm_type" }, + "emm_pct_emm_82": { "source_id": "emm_type" }, + "emm_pct_emm_83": { "source_id": "emm_type" }, + "emm_pct_emm_89": { "source_id": "emm_type" }, + "emm_pct_emm_91": { "source_id": "emm_type" }, + "emm_pct_emm_92": { "source_id": "emm_type" }, + "emm_pct_other": { "source_id": "emm_type" }, + "emm_count_number_of_isolates": { "source_id": "n_isolates" } + } + }, + + "bundle_gas/dist/abcs_gas_emm.parquet|value": { + "short_name": "Value", + "long_name": "emm type percent, or isolate count", + "short_description": "Percent of invasive GAS isolates of the emm type named in `measure`; or the isolate count.", + "long_description": "For the `emm_pct_*` measures, the annual percent of invasive Group A Streptococcus isolates belonging to the named emm type (surface protein gene sequence type), with `emm_pct_other` collecting all types not individually reported. emm typing tracks GAS strain diversity and prospective vaccine coverage. For `emm_count_number_of_isolates`, the number of isolates typed (the denominator), which is a count rather than a percent. Not every emm type is reported in every year, so this file is sparse; missing combinations are dropped rather than zero-filled.", + "measure_type": "Mixed", + "unit": "percent or count", + "time_resolution": "Year", + "sources": [{ "id": "abcs_gas" }] + }, + + "_bundle": { + "name": "bundle_gas", + "sources": ["abcs_gas", "epic_gas", "nnds"], + "dist_files": { + "epic_gas.parquet": { + "sources": ["epic_gas"], + "source_files": ["epic_gas/standard/data.csv.gz"] + }, + "nnds_stss.parquet": { + "sources": ["nnds"], + "source_files": ["nnds/standard/data.csv.gz"] + }, + "abcs_gas.parquet": { + "sources": ["abcs_gas"], + "source_files": ["abcs_gas/standard/data.csv.gz"] + }, + "abcs_gas_syndromes.parquet": { + "sources": ["abcs_gas"], + "source_files": ["abcs_gas/standard/data_syndromes.csv.gz"] + }, + "abcs_gas_resistance.parquet": { + "sources": ["abcs_gas"], + "source_files": ["abcs_gas/standard/data_resistance.csv.gz"] + }, + "abcs_gas_emm.parquet": { + "sources": ["abcs_gas"], + "source_files": ["abcs_gas/standard/data_emm.csv.gz"] + } + } + } +} diff --git a/data/bundle_gas/process.json b/data/bundle_gas/process.json new file mode 100644 index 000000000..312005944 --- /dev/null +++ b/data/bundle_gas/process.json @@ -0,0 +1,42 @@ +{ + "name": "bundle_gas", + "type": "bundle", + "scripts": [ + { + "path": "build.R", + "last_run": "2026-08-05 16:02:57", + "run_time": 0.459, + "last_status": { + "log": ["", "Attaching package: 'dplyr'", "", "The following objects are masked from 'package:stats':", "", " filter, lag", "", "The following objects are masked from 'package:base':", "", " intersect, setdiff, setequal, union", "", "", "Attaching package: 'arrow'", "", "The following object is masked from 'package:utils':", "", " timestamp", "", "NNDSS: 27 of 12376 weekly increments are negative (downward revisions to the cumulative count); left as-is."], + "success": true + } + } + ], + "source_files": [ + "epic_gas/standard/data.csv.gz", + "nnds/standard/data.csv.gz", + "abcs_gas/standard/data.csv.gz", + "abcs_gas/standard/data_syndromes.csv.gz", + "abcs_gas/standard/data_resistance.csv.gz", + "abcs_gas/standard/data_emm.csv.gz" + ], + "dist_state": { + "./data/bundle_gas/dist/abcs_gas.parquet": "8f1bd8f1b36a7cb3bc3e730ce7f7da2f", + "./data/bundle_gas/dist/abcs_gas_emm.parquet": "9556e06c17ba3c806bafc11f8aa640c9", + "./data/bundle_gas/dist/abcs_gas_resistance.parquet": "1a3d0d49f5e7edc1eab032aaa7819d09", + "./data/bundle_gas/dist/abcs_gas_syndromes.parquet": "bec72a801bba5023cfb43a5e977c81d0", + "./data/bundle_gas/dist/epic_gas.parquet": "0c5e4ed0b05c939c9bc985a6f04344dd", + "./data/bundle_gas/dist/nnds_stss.parquet": "9100d85a0adf1dd9efcedbb7a942d533", + "./data/epic_gas/standard/datapackage.json": "dffc76f5b34bd5e5c8ed685b80954f69", + "./data/nnds/standard/datapackage.json": "fdd44b854a58af372c1a67befb4c98dd", + "./data/abcs_gas/standard/datapackage.json": "3326cf2b8704378ec58521b2dbdcc045" + }, + "standard_state": { + "./data/epic_gas/standard/data.csv.gz": "e4c628211a213d25b38fc561d40d4563", + "./data/nnds/standard/data.csv.gz": "b93290fa03c9325086af9c31d7cd0a8c", + "./data/abcs_gas/standard/data.csv.gz": "7d964cd8f86b3257944c20dd618dd647", + "./data/abcs_gas/standard/data_syndromes.csv.gz": "cd8c50386db2435e920a57ada9f4a806", + "./data/abcs_gas/standard/data_resistance.csv.gz": "f433dda532d697ecde3015d579b41a55", + "./data/abcs_gas/standard/data_emm.csv.gz": "4d3a3d6efeece00e448c5327cb56a8b7" + } +} diff --git a/docs/index.html b/docs/index.html index 43a9a1c0d..fc893e14f 100644 --- a/docs/index.html +++ b/docs/index.html @@ -33,9 +33,15 @@
Data Sources
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Area Health Resource File

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The Area Health Resource File (AHRF) is an annual county-level database produced by the Health Resources and Services Administration (HRSA). It aggregates data from over 50 sources including the AMA Physician Masterfile, the American Hospital Association Annual Survey, the Bureau of Health Workforce, CMS Medicare claims, the Census Bureau, and EPA air quality monitoring. The AHRF covers all U.S. counties and territories with measures of health workforce supply, health facility counts, demographics, socioeconomic conditions, health expenditures, and environmental factors. It is widely used in health services research to characterize county-level resource availability and identify shortage areas.

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Abcs Gas

+

CDC monitors invasive bacterial infections through Active Bacterial Core surveillance (ABCs), a population-based surveillance program for invasive bacterial diseases in selected geographic areas of the United States. This dataset reports annual data on invasive Group A Streptococcus (iGAS) disease from 1997 onwards, including case and death rates by age group, sex, and race; clinical syndrome distribution (cellulitis, bacteremia without focus, pneumonia, necrotizing fasciitis, streptococcal toxic shock syndrome); antibiotic resistance patterns; and emm type distribution among isolates. ABCs catchment areas include California, Colorado, Connecticut, Georgia, Maryland, Minnesota, New York, Oregon, and Tennessee, representing approximately 10% of the US population. Incidence rates are calculated using U.S. Census Bureau population estimates for the respective catchment areas.

Sources
Restrictions: - Public domain. HRSA data is produced by a U.S. federal agency and is generally not subject to copyright restrictions. + Public domain. CDC data is generally not subject to copyright restrictions.

Variables

@@ -464,176 +589,663 @@
- ahrf_hpsa_prim_care - - HPSA: Primary Care - Federal HPSA designation indicating primary care provider shortages. - Category - Designation code (0=none, 1=whole county, 2=partial county) - - - - ahrf_hpsa_dental - - HPSA: Dental - Federal HPSA designation indicating dental provider shortages. - Category - Designation code (0=none, 1=whole county, 2=partial county) - - - - ahrf_hpsa_mental_health - - HPSA: Mental Health - Federal HPSA designation indicating mental health provider shortages. - Category - Designation code (0=none, 1=whole county, 2=partial county) - - - - ahrf_rural_urban_code - - Rural-Urban Code - USDA rural-urban continuum code classifying counties from metro to rural (1–9). - Category - Code 1–9 (1=large metro, 9=most rural) - - - - ahrf_md_all - - Total MDs in Patient Care - Count of non-federal MDs across all specialties in patient care roles. - Count - Physicians - - - - ahrf_psych - - Psychiatrists - Count of non-federal adult psychiatrists. - Count - Psychiatrists - - - - ahrf_hospitals - - Hospitals (Count) - Total number of hospitals in the county. - Count - Hospitals - - - - ahrf_population - - Population - Total county resident population estimate. - Count - Persons - - - - ahrf_pop_density - - Population Density - County population density per square mile from Census data. - Rate - Persons per square mile - - - - ahrf_critical_access_hosp + age - Critical Access Hospitals - Number of Medicare-certified critical access hospitals in the county. - Count - Critical access hospitals + Age Group + Age group category + category + - ahrf_pcp + sex - Primary Care Physicians - Count of non-federal primary care physicians (MDs and DOs) in patient care roles, excluding hospital residents. - Count - Physicians + Sex + Sex category (Male, Female, Overall) + category + - ahrf_dentists + race_ethnicity - Dentists (NPI Count) - Count of dentists with an active NPI in the county. - Count - Dentists + Race/Ethnicity + Race/ethnicity category + category + - ahrf_good_air_pct + abcs_gas_rate_cases - Good Air Quality (%) - Percentage of measured days rated 'Good' by EPA Air Quality Index. - Percent - Percent + abcs_gas_rate_cases + + + - ahrf_pm25 + abcs_gas_rate_deaths - PM2.5 Annual Avg - Annual average PM2.5 concentration (μg/m³) from EPA monitoring data. - Rate - μg/m³ + abcs_gas_rate_deaths + + + - ahrf_medicare_per_capita + abcs_gas_N_cases - Medicare Per Capita Cost - Actual Medicare FFS per capita spending for county residents. - Rate - Dollars per Medicare FFS enrollee + abcs_gas_N_cases + + + - ahrf_ed_per_1k_medicare + abcs_gas_N_deaths - ED Visits per 1k Medicare - County ED visit rate among traditional Medicare fee-for-service enrollees. - Rate - ED visits per 1,000 Medicare FFS beneficiaries + abcs_gas_N_deaths + + + -
-
-

Atlas AMR

-

No standard data files found.

-
-
-

Beam

-

The BEAM Dashboard is an interactive tool built on the System for Enteric Disease Response, Investigation, and Coordination (SEDRIC) that provides timely data on enteric pathogen trends and serotype details to support prevention of illnesses from food, water, and animal contact. This source uses the state-level 'Report Data' export (dataset jbhn-e8xn) rather than the HHS-region export, so isolate counts can be represented with standard state FIPS codes. Raw records are aggregated across source type (human, food, animal, environment), source site, and serotype/species to produce a monthly isolate count per state and pathogen. National values are computed by PopHIVE/Ingest as the sum across all reporting states. Isolate rates per 100,000 population use a single 2021 Census population denominator for all years. Counts reflect isolates sequenced and reported by participating state and local public health laboratories, which varies by jurisdiction and pathogen, so trends should not be interpreted as complete disease incidence.

-
Sources
- -
- Restrictions: - Public domain. CDC data is generally not subject to copyright restrictions. -
-

Variables

- data.csv.gz + data_emm.csv.gz +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VariableShort NameDescriptionTypeUnit
+ geography + GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
+ time + TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
+ abcs_gas_emm_count_number_of_isolates + abcs_gas_emm_count_number_of_isolates
+ abcs_gas_emm_pct_other + abcs_gas_emm_pct_other
+ abcs_gas_emm_pct_emm_1 + abcs_gas_emm_pct_emm_1
+ abcs_gas_emm_pct_emm_11 + abcs_gas_emm_pct_emm_11
+ abcs_gas_emm_pct_emm_12 + abcs_gas_emm_pct_emm_12
+ abcs_gas_emm_pct_emm_28 + abcs_gas_emm_pct_emm_28
+ abcs_gas_emm_pct_emm_43 + abcs_gas_emm_pct_emm_43
+ abcs_gas_emm_pct_emm_59 + abcs_gas_emm_pct_emm_59
+ abcs_gas_emm_pct_emm_77 + abcs_gas_emm_pct_emm_77
+ abcs_gas_emm_pct_emm_82 + abcs_gas_emm_pct_emm_82
+ abcs_gas_emm_pct_emm_83 + abcs_gas_emm_pct_emm_83
+ abcs_gas_emm_pct_emm_89 + abcs_gas_emm_pct_emm_89
+ abcs_gas_emm_pct_emm_92 + abcs_gas_emm_pct_emm_92
+ abcs_gas_emm_pct_emm_49 + abcs_gas_emm_pct_emm_49
+ abcs_gas_emm_pct_emm_81 + abcs_gas_emm_pct_emm_81
+ abcs_gas_emm_pct_emm_60 + abcs_gas_emm_pct_emm_60
+ abcs_gas_emm_pct_emm_91 + abcs_gas_emm_pct_emm_91
+
+
+ data_resistance.csv.gz +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VariableShort NameDescriptionTypeUnit
+ geography + GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
+ time + TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
+ abcs_gas_pct_resistant_cefotaxime + abcs_gas_pct_resistant_cefotaxime
+ abcs_gas_pct_resistant_clindamycin + abcs_gas_pct_resistant_clindamycin
+ abcs_gas_pct_resistant_erythromycin + abcs_gas_pct_resistant_erythromycin
+ abcs_gas_pct_resistant_penicillin + abcs_gas_pct_resistant_penicillin
+ abcs_gas_pct_resistant_tetracycline + abcs_gas_pct_resistant_tetracycline
+ abcs_gas_pct_resistant_vancomycin + abcs_gas_pct_resistant_vancomycin
+ abcs_gas_n_isolates + abcs_gas_n_isolates
+
+
+ data_syndromes.csv.gz +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VariableShort NameDescriptionTypeUnit
+ geography + GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
+ time + TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
+ abcs_gas_pct_syndrome_cellulitis + abcs_gas_pct_syndrome_cellulitis
+ abcs_gas_pct_syndrome_bacteremia_without_focus + abcs_gas_pct_syndrome_bacteremia_without_focus
+ abcs_gas_pct_syndrome_pneumonia + abcs_gas_pct_syndrome_pneumonia
+ abcs_gas_pct_syndrome_necrotizing_fasciitis + abcs_gas_pct_syndrome_necrotizing_fasciitis
+ abcs_gas_pct_syndrome_strep_toxic_shock + abcs_gas_pct_syndrome_strep_toxic_shock
+
+
+
+

Area Health Resource File

+

The Area Health Resource File (AHRF) is an annual county-level database produced by the Health Resources and Services Administration (HRSA). It aggregates data from over 50 sources including the AMA Physician Masterfile, the American Hospital Association Annual Survey, the Bureau of Health Workforce, CMS Medicare claims, the Census Bureau, and EPA air quality monitoring. The AHRF covers all U.S. counties and territories with measures of health workforce supply, health facility counts, demographics, socioeconomic conditions, health expenditures, and environmental factors. It is widely used in health services research to characterize county-level resource availability and identify shortage areas.

+
Sources
+ +
+ Restrictions: + Public domain. HRSA data is produced by a U.S. federal agency and is generally not subject to copyright restrictions. +
+

Variables

+
+ data.csv.gz +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VariableShort NameDescriptionTypeUnit
+ geography + GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
+ time + TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
+ ahrf_hpsa_prim_care + HPSA: Primary CareFederal HPSA designation indicating primary care provider shortages.CategoryDesignation code (0=none, 1=whole county, 2=partial county)
+ ahrf_hpsa_dental + HPSA: DentalFederal HPSA designation indicating dental provider shortages.CategoryDesignation code (0=none, 1=whole county, 2=partial county)
+ ahrf_hpsa_mental_health + HPSA: Mental HealthFederal HPSA designation indicating mental health provider shortages.CategoryDesignation code (0=none, 1=whole county, 2=partial county)
+ ahrf_rural_urban_code + Rural-Urban CodeUSDA rural-urban continuum code classifying counties from metro to rural (1–9).CategoryCode 1–9 (1=large metro, 9=most rural)
+ ahrf_md_all + Total MDs in Patient CareCount of non-federal MDs across all specialties in patient care roles.CountPhysicians
+ ahrf_psych + PsychiatristsCount of non-federal adult psychiatrists.CountPsychiatrists
+ ahrf_hospitals + Hospitals (Count)Total number of hospitals in the county.CountHospitals
+ ahrf_population + PopulationTotal county resident population estimate.CountPersons
+ ahrf_pop_density + Population DensityCounty population density per square mile from Census data.RatePersons per square mile
+ ahrf_critical_access_hosp + Critical Access HospitalsNumber of Medicare-certified critical access hospitals in the county.CountCritical access hospitals
+ ahrf_pcp + Primary Care PhysiciansCount of non-federal primary care physicians (MDs and DOs) in patient care roles, excluding hospital residents.CountPhysicians
+ ahrf_dentists + Dentists (NPI Count)Count of dentists with an active NPI in the county.CountDentists
+ ahrf_good_air_pct + Good Air Quality (%)Percentage of measured days rated 'Good' by EPA Air Quality Index.PercentPercent
+ ahrf_pm25 + PM2.5 Annual AvgAnnual average PM2.5 concentration (μg/m³) from EPA monitoring data.Rateμg/m³
+ ahrf_medicare_per_capita + Medicare Per Capita CostActual Medicare FFS per capita spending for county residents.RateDollars per Medicare FFS enrollee
+ ahrf_ed_per_1k_medicare + ED Visits per 1k MedicareCounty ED visit rate among traditional Medicare fee-for-service enrollees.RateED visits per 1,000 Medicare FFS beneficiaries
+
+
+
+

Atlas AMR

+

No standard data files found.

+
+
+

Beam

+

The BEAM Dashboard is an interactive tool built on the System for Enteric Disease Response, Investigation, and Coordination (SEDRIC) that provides timely data on enteric pathogen trends and serotype details to support prevention of illnesses from food, water, and animal contact. This source uses the state-level 'Report Data' export (dataset jbhn-e8xn) rather than the HHS-region export, so isolate counts can be represented with standard state FIPS codes. Raw records are aggregated across source type (human, food, animal, environment), source site, and serotype/species to produce a monthly isolate count per state and pathogen. National values are computed by PopHIVE/Ingest as the sum across all reporting states. Isolate rates per 100,000 population use a single 2021 Census population denominator for all years. Counts reflect isolates sequenced and reported by participating state and local public health laboratories, which varies by jurisdiction and pathogen, so trends should not be interpreted as complete disease incidence.

+
Sources
+ +
+ Restrictions: + Public domain. CDC data is generally not subject to copyright restrictions. +
+

Variables

+
+ data.csv.gz
@@ -822,6 +1434,195 @@
Sources
Public domain. CDC data is generally not subject to copyright restrictions.

Variables

+
+ data.csv.gz +
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VariableShort NameDescriptionTypeUnit
+ time + TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
+ age + AgeAge group.integeryears
+ geography + GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
+ pct_depression_sample_size + Sample sizeSurvey sample size used to estimate depression.integercount
+ pct_depression_value + ValuePercent of the population with depression.percentpercent
+ pct_depression_value_lcl + Lower 95% CILower bound of the 95% confidence interval for percent depression.percentpercent
+ pct_depression_value_ucl + Upper 95% CIUpper bound of the 95% confidence interval for percent depression.percentpercent
+ pct_diabetes_sample_size + Sample sizeSurvey sample size used to estimate diabetes.integercount
+ pct_diabetes_value + ValuePercent of the population with diabetes.percentpercent
+ pct_diabetes_value_lcl + Lower 95% CILower bound of the 95% confidence interval for percent diabetes.percentpercent
+ pct_diabetes_value_ucl + Upper 95% CIUpper bound of the 95% confidence interval for percent diabetes.percentpercent
+ pct_heavy_drink_sample_size + Sample sizeSurvey sample size used to estimate heavy_drink.integercount
+ pct_heavy_drink_value + ValuePercent of the population with heavy_drink.percentpercent
+ pct_heavy_drink_value_lcl + Lower 95% CILower bound of the 95% confidence interval for percent heavy_drink.percentpercent
+ pct_heavy_drink_value_ucl + Upper 95% CIUpper bound of the 95% confidence interval for percent heavy_drink.percentpercent
+ pct_obesity_sample_size + Sample sizeSurvey sample size used to estimate obesity.integercount
+ pct_obesity_value + ValuePercent of the population with obesity.percentpercent
+ pct_obesity_value_lcl + Lower 95% CILower bound of the 95% confidence interval for percent obesity.percentpercent
+ pct_obesity_value_ucl + Upper 95% CIUpper bound of the 95% confidence interval for percent obesity.percentpercent
+
data_survey.csv.gz
@@ -948,195 +1749,6 @@
-
- data.csv.gz -
-
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
VariableShort NameDescriptionTypeUnit
- time - TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
- age - AgeAge group.integeryears
- geography - GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
- pct_depression_sample_size - Sample sizeSurvey sample size used to estimate depression.integercount
- pct_depression_value - ValuePercent of the population with depression.percentpercent
- pct_depression_value_lcl - Lower 95% CILower bound of the 95% confidence interval for percent depression.percentpercent
- pct_depression_value_ucl - Upper 95% CIUpper bound of the 95% confidence interval for percent depression.percentpercent
- pct_diabetes_sample_size - Sample sizeSurvey sample size used to estimate diabetes.integercount
- pct_diabetes_value - ValuePercent of the population with diabetes.percentpercent
- pct_diabetes_value_lcl - Lower 95% CILower bound of the 95% confidence interval for percent diabetes.percentpercent
- pct_diabetes_value_ucl - Upper 95% CIUpper bound of the 95% confidence interval for percent diabetes.percentpercent
- pct_heavy_drink_sample_size - Sample sizeSurvey sample size used to estimate heavy_drink.integercount
- pct_heavy_drink_value - ValuePercent of the population with heavy_drink.percentpercent
- pct_heavy_drink_value_lcl - Lower 95% CILower bound of the 95% confidence interval for percent heavy_drink.percentpercent
- pct_heavy_drink_value_ucl - Upper 95% CIUpper bound of the 95% confidence interval for percent heavy_drink.percentpercent
- pct_obesity_sample_size - Sample sizeSurvey sample size used to estimate obesity.integercount
- pct_obesity_value - ValuePercent of the population with obesity.percentpercent
- pct_obesity_value_lcl - Lower 95% CILower bound of the 95% confidence interval for percent obesity.percentpercent
- pct_obesity_value_ucl - Upper 95% CIUpper bound of the 95% confidence interval for percent obesity.percentpercent
-

CDC Cfa Rt

@@ -4875,7 +5487,7 @@
Sources

Variables

- data_state_county_age_by_race.csv.gz + data_state_county_age.csv.gz
@@ -5352,7 +5964,7 @@
- data_state_county_age_by_sex.csv.gz + data_state_county_age_by_race.csv.gz
@@ -5829,7 +6441,7 @@
- data_state_county_age.csv.gz + data_state_county_age_by_sex.csv.gz
@@ -10431,7 +11043,159 @@
- weekly_tests.csv.gz + weekly_tests.csv.gz +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VariableShort NameDescriptionTypeUnit
+ geography + GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
+ time + TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
+ epic_n_all_diarrhea + Diarrhea Encounters (All Encounters)Number of encounters (any type, not just ED) with all-cause diarrhea diagnoses.Countencounters
+ epic_n_encounters_total_weekly + All Encounters (Any Reason, Weekly)Total number of weekly encounters for any reason.Countencounters
+ epic_n_cyclospora_positive + Cyclospora Positive EncountersNumber of encounters with an abnormal (positive) cyclospora lab result.Countencounters
+ epic_n_cyclospora_tested + Cyclospora Tests PerformedNumber of encounters with a cyclospora lab test performed, regardless of result.Countencounters
+ epic_pct_cyclospora_positive + Cyclospora Percent PositivePercent of cyclospora lab tests with an abnormal (positive) result.Percent%
+ epic_pct_cyclospora_tested + Percent Tested for CyclosporaPercent of all encounters that included a cyclospora lab test.Percent%
+ epic_pct_all_diarrhea + Diarrhea Encounters (All Encounters, %)Percentage of all encounters (any type) attributable to all-cause diarrhea.Percent%
+ epic_suppressed_flag_all_diarrhea + All-Encounters Diarrhea Count Suppressed?Binary indicator: 1 if the all-encounters diarrhea count was suppressed, 0 otherwise.binary
+ epic_suppressed_flag_encounters_total_weekly + Total Weekly Encounters Count Suppressed?Binary indicator: 1 if the total weekly encounter count was suppressed, 0 otherwise.binary
+ epic_suppressed_flag_cyclospora_positive + Cyclospora Positive Count Suppressed?Binary indicator: 1 if the cyclospora-positive encounter count was suppressed, 0 otherwise.binary
+ epic_suppressed_flag_cyclospora_tested + Cyclospora Tested Count Suppressed?Binary indicator: 1 if the cyclospora-tested encounter count was suppressed, 0 otherwise.binary
+
+
+
+

Epic Gas

+

Epic Cosmos is a collaborative research platform containing de-identified patient data from over 300 million patients across more than 1,600 hospitals and health systems using Epic electronic health record systems. Data is accessed via SlicerDicer, a self-service analytics tool. The dataset includes emergency department visits, diagnoses, immunizations, laboratory results, and other clinical data. Due to privacy protections, counts fewer than 10 are suppressed and imputed. Coverage extends across all U.S. states and territories. Note that county-level and city-level stratifications could differ markedly in total sample size due to high levels of missingness of county data in some states.

+
Sources
+ +
+ Restrictions: + The data can be re-used with appropriate attribution. A suggested citation relating to this data is 'Results of research performed with Epic Cosmos were obtained from the PopHIVE platform (https://github.com/PopHIVE/Ingest).' +
+

Variables

+
+ data.csv.gz
@@ -10465,102 +11229,57 @@
- - - - - - - - - - - + + + + - - + + - - - - - - - - - - - - - - - + - - + + - - - - - - - - - - - - - - - - - - + + + + - - - - + + + + - - - - + + + +
- epic_n_all_diarrhea - Diarrhea Encounters (All Encounters)Number of encounters (any type, not just ED) with all-cause diarrhea diagnoses.Countencounters
- epic_n_encounters_total_weekly + age All Encounters (Any Reason, Weekly)Total number of weekly encounters for any reason.CountencountersAge GroupAge group categorycategory
- epic_n_cyclospora_positive + epic_n_strep_throat Cyclospora Positive EncountersNumber of encounters with an abnormal (positive) cyclospora lab result.Strep Throat PatientsQuarterly count of patients with a strep throat diagnosis (J02.0, J03.00, J03.01). Countencounters
- epic_n_cyclospora_tested - Cyclospora Tests PerformedNumber of encounters with a cyclospora lab test performed, regardless of result.Countencounters
- epic_pct_cyclospora_positive - Cyclospora Percent PositivePercent of cyclospora lab tests with an abnormal (positive) result.Percent%patients
- epic_pct_cyclospora_tested + epic_pct_strep_throat Percent Tested for CyclosporaPercent of all encounters that included a cyclospora lab test.Strep Throat PercentageQuarterly percent of patients with a strep throat diagnosis (J02.0, J03.00, J03.01). Percent%
- epic_pct_all_diarrhea - Diarrhea Encounters (All Encounters, %)Percentage of all encounters (any type) attributable to all-cause diarrhea. Percent%
- epic_suppressed_flag_all_diarrhea - All-Encounters Diarrhea Count Suppressed?Binary indicator: 1 if the all-encounters diarrhea count was suppressed, 0 otherwise.binary
- epic_suppressed_flag_encounters_total_weekly + epic_strep_throat_suppressed_flag Total Weekly Encounters Count Suppressed?Binary indicator: 1 if the total weekly encounter count was suppressed, 0 otherwise.binarySuppressed flag: strep throatIndicates whether the strep throat numerator was suppressed and imputed; applies to both epic_n_strep_throat and epic_pct_strep_throat.Binary0/1
- epic_suppressed_flag_cyclospora_positive + epic_n_patients Cyclospora Positive Count Suppressed?Binary indicator: 1 if the cyclospora-positive encounter count was suppressed, 0 otherwise.binaryTotal PatientsQuarterly total patient count used as the denominator for the strep throat percentage.Countpatients
- epic_suppressed_flag_cyclospora_tested + epic_n_patients_suppressed_flag Cyclospora Tested Count Suppressed?Binary indicator: 1 if the cyclospora-tested encounter count was suppressed, 0 otherwise.binarySuppressed flag: total patientsIndicates whether the total patient count was suppressed and imputed.Binary0/1
@@ -11524,7 +12243,7 @@
Sources

Variables

- data_dma_year.csv.gz + data.csv.gz
@@ -11558,82 +12277,82 @@
- - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + @@ -11646,6 +12365,15 @@
+ + + + + + +
- gtrends_drug+overdose + gtrends_rsv_vaccine Google Search Volume: Drug OverdoseGoogle search volume for the term drug overdose.Google Search Volume: rsv_vaccineGoogle search volume of the term rsv_vaccine. probability probability * 10M
- gtrends_naloxone + gtrends_9mm Google Search Volume: naloxoneGoogle search volume of the term naloxone.Google Search Volume: 9mmGoogle search volume for the term 9mm. probability probability * 10M
- gtrends_narcan + gtrends_naloxone Google Search Volume: narcanGoogle search volume of the term narcan.Google Search Volume: naloxoneGoogle search volume of the term naloxone. probability probability * 10M
- gtrends_overdose + gtrends_drug+overdose Google Search Volume: overdoseGoogle search volume of the term overdose.Google Search Volume: Drug OverdoseGoogle search volume for the term drug overdose. probability probability * 10M
- gtrends_rsv_vaccine + gtrends_heat+exhaustion Google Search Volume: rsv_vaccineGoogle search volume of the term rsv_vaccine.Google Search Volume: Heat ExhaustionGoogle search volume for the term heat exhaustion. probability probability * 10M
- gtrends_rsv + gtrends_heat+stroke Google Search Volume: rsvGoogle search volume of the term rsv.Google Search Volume: Heat StrokeGoogle search volume for the term heat stroke. probability probability * 10M
- gtrends_heat+exhaustion + gtrends_narcan Google Search Volume: Heat ExhaustionGoogle search volume for the term heat exhaustion.Google Search Volume: narcanGoogle search volume of the term narcan. probability probability * 10M
- gtrends_heat+stroke + gtrends_overdose Google Search Volume: Heat StrokeGoogle search volume for the term heat stroke.Google Search Volume: overdoseGoogle search volume of the term overdose. probability probability * 10M
- gtrends_9mm + gtrends_rsv Google Search Volume: 9mmGoogle search volume for the term 9mm.Google Search Volume: rsvGoogle search volume of the term rsv. probability probability * 10M
probability probability * 10M
+ gtrends_rsv_adjusted + Google Search Volume: rsv_adjustedGoogle search volume of the term rsv_adjusted.probabilityprobability * 10M
@@ -11776,7 +12504,7 @@
- data_year.csv.gz + data_dma_year.csv.gz
@@ -11810,19 +12538,10 @@
- - - - - - - - - + + @@ -11837,73 +12556,73 @@
- - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + @@ -11911,7 +12630,7 @@
- gtrends_rsv_vaccine - Google Search Volume: rsv_vaccineGoogle search volume of the term rsv_vaccine.probabilityprobability * 10M
- gtrends_9mm + gtrends_drug+overdose Google Search Volume: 9mmGoogle search volume for the term 9mm.Google Search Volume: Drug OverdoseGoogle search volume for the term drug overdose. probability probability * 10M
- gtrends_drug+overdose + gtrends_narcan Google Search Volume: Drug OverdoseGoogle search volume for the term drug overdose.Google Search Volume: narcanGoogle search volume of the term narcan. probability probability * 10M
- gtrends_heat+exhaustion + gtrends_overdose Google Search Volume: Heat ExhaustionGoogle search volume for the term heat exhaustion.Google Search Volume: overdoseGoogle search volume of the term overdose. probability probability * 10M
- gtrends_heat+stroke + gtrends_rsv_vaccine Google Search Volume: Heat StrokeGoogle search volume for the term heat stroke.Google Search Volume: rsv_vaccineGoogle search volume of the term rsv_vaccine. probability probability * 10M
- gtrends_narcan + gtrends_rsv Google Search Volume: narcanGoogle search volume of the term narcan.Google Search Volume: rsvGoogle search volume of the term rsv. probability probability * 10M
- gtrends_overdose + gtrends_heat+exhaustion Google Search Volume: overdoseGoogle search volume of the term overdose.Google Search Volume: Heat ExhaustionGoogle search volume for the term heat exhaustion. probability probability * 10M
- gtrends_rsv + gtrends_heat+stroke Google Search Volume: rsvGoogle search volume of the term rsv.Google Search Volume: Heat StrokeGoogle search volume for the term heat stroke. probability probability * 10M
- gtrends_shotgun + gtrends_9mm Google Search Volume: ShotgunGoogle search volume for the term shotgun.Google Search Volume: 9mmGoogle search volume for the term 9mm. probability probability * 10M
- gtrends_rsv_adjusted + gtrends_shotgun Google Search Volume: rsv_adjustedGoogle search volume of the term rsv_adjusted.Google Search Volume: ShotgunGoogle search volume for the term shotgun. probability probability * 10M
- data.csv.gz + data_year.csv.gz
@@ -12305,7 +13024,7 @@
Sources

Variables

- data_county.csv.gz + data.csv.gz
@@ -12350,7 +13069,7 @@
- data_state.csv.gz + data_county.csv.gz
@@ -12395,7 +13114,7 @@
- data.csv.gz + data_state.csv.gz
@@ -16521,294 +17240,6 @@
Sources

Variables

-
- data_county.csv.gz -
-
-
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
VariableShort NameDescriptionTypeUnit
- geography - GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
- time - TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
- n_deaths_overdose - Drug overdose deathsProvisional count of drug overdose deaths. State-level data are 12-month rolling totals; county-level data are monthly.CountDeaths
- suppressed - Drug overdose suppression flagIndicates whether the county drug overdose death count was suppressed by NCHS. Due to privacy protections, counts fewer than 10 are suppressed and imputed to be 5.BinaryBinary indicator
- pct_pending_invest - Percent pending investigationPercentage of death records still pending investigation for the reporting period.PercentPercent
-
-
- data_state_21_causes.csv.gz -
-
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
VariableShort NameDescriptionTypeUnit
- geography - GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
- time - TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
- rate_all_causes - All-cause mortality rateQuarterly age-adjusted death rate from all causes per 100,000 population.RateDeaths per 100,000
- rate_alzheimer_disease - Alzheimer's mortality rateQuarterly age-adjusted death rate from Alzheimer's disease per 100,000 population.RateDeaths per 100,000
- rate_covid_19 - COVID-19 mortality rateQuarterly age-adjusted death rate from COVID-19 per 100,000 population.RateDeaths per 100,000
- rate_cancer - Cancer mortality rateQuarterly age-adjusted death rate from cancer per 100,000 population.RateDeaths per 100,000
- rate_chronic_liver_disease_and_cirrhosis - Liver disease mortality rateQuarterly age-adjusted death rate from chronic liver disease and cirrhosis per 100,000 population.RateDeaths per 100,000
- rate_chronic_lower_respiratory_diseases - CLRD mortality rateQuarterly age-adjusted death rate from chronic lower respiratory diseases per 100,000 population.RateDeaths per 100,000
- rate_diabetes - Diabetes mortality rateQuarterly age-adjusted death rate from diabetes per 100,000 population.RateDeaths per 100,000
- rate_drug_overdose - Drug overdose mortality rateQuarterly age-adjusted death rate from drug overdose per 100,000 population.RateDeaths per 100,000
- rate_falls_ages_65_and_over - Falls mortality rate (65+)Quarterly age-adjusted death rate from falls among adults 65 and over per 100,000 population.RateDeaths per 100,000
- rate_firearm_related_injury - Firearm injury mortality rateQuarterly age-adjusted death rate from firearm-related injuries per 100,000 population.RateDeaths per 100,000
- rate_heart_disease - Heart disease mortality rateQuarterly age-adjusted death rate from heart disease per 100,000 population.RateDeaths per 100,000
- rate_hiv_disease - HIV mortality rateQuarterly age-adjusted death rate from HIV disease per 100,000 population.RateDeaths per 100,000
- rate_homicide - Homicide mortality rateQuarterly age-adjusted death rate from homicide per 100,000 population.RateDeaths per 100,000
- rate_hypertension - Hypertension mortality rateQuarterly age-adjusted death rate from hypertension per 100,000 population.RateDeaths per 100,000
- rate_influenza_and_pneumonia - Flu & pneumonia mortality rateQuarterly age-adjusted death rate from influenza and pneumonia per 100,000 population.RateDeaths per 100,000
- rate_kidney_disease - Kidney disease mortality rateQuarterly age-adjusted death rate from kidney disease per 100,000 population.RateDeaths per 100,000
- rate_parkinson_disease - Parkinson's mortality rateQuarterly age-adjusted death rate from Parkinson's disease per 100,000 population.RateDeaths per 100,000
- rate_pneumonitis_due_to_solids_and_liquids - Aspiration pneumonitis mortality rateQuarterly age-adjusted death rate from pneumonitis due to solids and liquids per 100,000 population.RateDeaths per 100,000
- rate_stroke - Stroke mortality rateQuarterly age-adjusted death rate from stroke per 100,000 population.RateDeaths per 100,000
- rate_suicide - Suicide mortality rateQuarterly age-adjusted death rate from suicide per 100,000 population.RateDeaths per 100,000
- rate_unintentional_injuries - Unintentional injury mortality rateQuarterly age-adjusted death rate from unintentional injuries per 100,000 population.RateDeaths per 100,000
-
data.csv.gz
@@ -16971,27 +17402,71 @@
-
-
-

Neiss

-

NEISS is a national probability sample of hospital emergency departments (~100 of the ~5,000+ U.S. hospitals with 24-hour EDs) operated by the U.S. Consumer Product Safety Commission. Each sampled record describes an injury treated in the ED, including patient age, sex, race, Hispanic ethnicity (added 2019), diagnosis, body part, disposition, up to three associated consumer products, and a statistical weight (plus sampling stratum and PSU). Sample weights scale records to national estimates; raw record counts are not nationally representative. This dataset covers treatment years from 2019 through the latest year CPSC has posted (auto-detected at ingest time), aggregated to national (geography='00') annual counts, in wide format: one neiss_n_ (raw sampled count) and one neiss_wt_ (weighted national estimate) column per primary-diagnosis or primary-product-group category. Product groups are reconstructed from NEISS product-code bands and are approximate, not an official CPSC taxonomy. Companion _rate files (data_*_rate.csv.gz) give injury rates per 100,000 population stratified by age and sex only, using the weighted estimate as numerator and a constant national age x sex population (mean of U.S. Census Vintage 2023 estimates, 2020-2023) as denominator.

-
Sources
- -
- Restrictions: - Public domain. NEISS data are produced by the U.S. Consumer Product Safety Commission and are generally not subject to copyright restrictions. +
+ data_county.csv.gz +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VariableShort NameDescriptionTypeUnit
+ geography + GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
+ time + TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
+ n_deaths_overdose + Drug overdose deathsProvisional count of drug overdose deaths. State-level data are 12-month rolling totals; county-level data are monthly.CountDeaths
+ suppressed + Drug overdose suppression flagIndicates whether the county drug overdose death count was suppressed by NCHS. Due to privacy protections, counts fewer than 10 are suppressed and imputed to be 5.BinaryBinary indicator
+ pct_pending_invest + Percent pending investigationPercentage of death records still pending investigation for the reporting period.PercentPercent
-

Variables

- data_agegroup_diagnosis_rate.csv.gz + data_state_21_causes.csv.gz
@@ -17025,295 +17500,215 @@
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - + - - + + - +
- age - AgePatient age: age in completed months (00-23 months) in the infant files; a standard age band in the age-group files.categoricalcategory
- sex - SexPatient sex (Male, Female, Unknown).categoricalcategory
- neiss_rate_amputation - Amputation injury rateAnnual ED injury visits with a primary diagnosis of amputation per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_anoxia - Anoxia injury rateAnnual ED injury visits with a primary diagnosis of anoxia per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_aspirated_object - Aspirated object injury rateAnnual ED injury visits with a primary diagnosis of aspirated object per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_avulsion - Avulsion injury rateAnnual ED injury visits with a primary diagnosis of avulsion per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_burns_chemical - Chemical burns injury rateAnnual ED injury visits with a primary diagnosis of chemical burns per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_burns_elec - Electrical burns injury rateAnnual ED injury visits with a primary diagnosis of electrical burns per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_burns_radiation - Radiation burns injury rateAnnual ED injury visits with a primary diagnosis of radiation burns per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_burns_scald - Scald burns injury rateAnnual ED injury visits with a primary diagnosis of scald burns per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_burns_thermal - Thermal burns injury rateAnnual ED injury visits with a primary diagnosis of thermal burns per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_concussion + rate_all_causes Concussion injury rateAnnual ED injury visits with a primary diagnosis of concussion per 100,000 U.S. population, by age and sex.All-cause mortality rateQuarterly age-adjusted death rate from all causes per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_contusion_or_abrasion + rate_alzheimer_disease Contusion or abrasion injury rateAnnual ED injury visits with a primary diagnosis of contusion or abrasion per 100,000 U.S. population, by age and sex.Alzheimer's mortality rateQuarterly age-adjusted death rate from Alzheimer's disease per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_crushing + rate_covid_19 Crushing injury injury rateAnnual ED injury visits with a primary diagnosis of crushing injury per 100,000 U.S. population, by age and sex.COVID-19 mortality rateQuarterly age-adjusted death rate from COVID-19 per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_dental_injury + rate_cancer Dental injury injury rateAnnual ED injury visits with a primary diagnosis of dental injury per 100,000 U.S. population, by age and sex.Cancer mortality rateQuarterly age-adjusted death rate from cancer per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_dermat_or_conj + rate_chronic_liver_disease_and_cirrhosis Dermatitis or conjunctivitis injury rateAnnual ED injury visits with a primary diagnosis of dermatitis or conjunctivitis per 100,000 U.S. population, by age and sex.Liver disease mortality rateQuarterly age-adjusted death rate from chronic liver disease and cirrhosis per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_dislocation + rate_chronic_lower_respiratory_diseases Dislocation injury rateAnnual ED injury visits with a primary diagnosis of dislocation per 100,000 U.S. population, by age and sex.CLRD mortality rateQuarterly age-adjusted death rate from chronic lower respiratory diseases per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_electric_shock + rate_diabetes Electric shock injury rateAnnual ED injury visits with a primary diagnosis of electric shock per 100,000 U.S. population, by age and sex.Diabetes mortality rateQuarterly age-adjusted death rate from diabetes per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_foreign_body + rate_drug_overdose Foreign body injury rateAnnual ED injury visits with a primary diagnosis of foreign body per 100,000 U.S. population, by age and sex.Drug overdose mortality rateQuarterly age-adjusted death rate from drug overdose per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_fracture + rate_falls_ages_65_and_over Fracture injury rateAnnual ED injury visits with a primary diagnosis of fracture per 100,000 U.S. population, by age and sex.Falls mortality rate (65+)Quarterly age-adjusted death rate from falls among adults 65 and over per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_hematoma + rate_firearm_related_injury Hematoma injury rateAnnual ED injury visits with a primary diagnosis of hematoma per 100,000 U.S. population, by age and sex.Firearm injury mortality rateQuarterly age-adjusted death rate from firearm-related injuries per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_hemorrhage + rate_heart_disease Hemorrhage injury rateAnnual ED injury visits with a primary diagnosis of hemorrhage per 100,000 U.S. population, by age and sex.Heart disease mortality rateQuarterly age-adjusted death rate from heart disease per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_ingested_object + rate_hiv_disease Ingested object injury rateAnnual ED injury visits with a primary diagnosis of ingested object per 100,000 U.S. population, by age and sex.HIV mortality rateQuarterly age-adjusted death rate from HIV disease per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_inter_organ_injury + rate_homicide Internal organ injury injury rateAnnual ED injury visits with a primary diagnosis of internal organ injury per 100,000 U.S. population, by age and sex.Homicide mortality rateQuarterly age-adjusted death rate from homicide per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_laceration + rate_hypertension Laceration injury rateAnnual ED injury visits with a primary diagnosis of laceration per 100,000 U.S. population, by age and sex.Hypertension mortality rateQuarterly age-adjusted death rate from hypertension per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_nerve_damage + rate_influenza_and_pneumonia Nerve damage injury rateAnnual ED injury visits with a primary diagnosis of nerve damage per 100,000 U.S. population, by age and sex.Flu & pneumonia mortality rateQuarterly age-adjusted death rate from influenza and pneumonia per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_other_or_not_stated + rate_kidney_disease Other or not stated injury rateAnnual ED injury visits with a primary diagnosis of other or not stated per 100,000 U.S. population, by age and sex.Kidney disease mortality rateQuarterly age-adjusted death rate from kidney disease per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_poisoning + rate_parkinson_disease Poisoning injury rateAnnual ED injury visits with a primary diagnosis of poisoning per 100,000 U.S. population, by age and sex.Parkinson's mortality rateQuarterly age-adjusted death rate from Parkinson's disease per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_puncture + rate_pneumonitis_due_to_solids_and_liquids Puncture injury rateAnnual ED injury visits with a primary diagnosis of puncture per 100,000 U.S. population, by age and sex.Aspiration pneumonitis mortality rateQuarterly age-adjusted death rate from pneumonitis due to solids and liquids per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_strain_sprain + rate_stroke Strain or sprain injury rateAnnual ED injury visits with a primary diagnosis of strain or sprain per 100,000 U.S. population, by age and sex.Stroke mortality rateQuarterly age-adjusted death rate from stroke per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_submersion + rate_suicide Submersion injury rateAnnual ED injury visits with a primary diagnosis of submersion per 100,000 U.S. population, by age and sex.Suicide mortality rateQuarterly age-adjusted death rate from suicide per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
- neiss_rate_burns_not_spec + rate_unintentional_injuries Burns (unspecified) injury rateAnnual ED injury visits with a primary diagnosis of burns (unspecified) per 100,000 U.S. population, by age and sex.Unintentional injury mortality rateQuarterly age-adjusted death rate from unintentional injuries per 100,000 population. RateInjuries per 100,000 populationDeaths per 100,000
+
+
+

Neiss

+

NEISS is a national probability sample of hospital emergency departments (~100 of the ~5,000+ U.S. hospitals with 24-hour EDs) operated by the U.S. Consumer Product Safety Commission. Each sampled record describes an injury treated in the ED, including patient age, sex, race, Hispanic ethnicity (added 2019), diagnosis, body part, disposition, up to three associated consumer products, and a statistical weight (plus sampling stratum and PSU). Sample weights scale records to national estimates; raw record counts are not nationally representative. This dataset covers treatment years from 2019 through the latest year CPSC has posted (auto-detected at ingest time), aggregated to national (geography='00') annual counts, in wide format: one neiss_n_ (raw sampled count) and one neiss_wt_ (weighted national estimate) column per primary-diagnosis or primary-product-group category. Product groups are reconstructed from NEISS product-code bands and are approximate, not an official CPSC taxonomy. Companion _rate files (data_*_rate.csv.gz) give injury rates per 100,000 population stratified by age and sex only, using the weighted estimate as numerator and a constant national age x sex population (mean of U.S. Census Vintage 2023 estimates, 2020-2023) as denominator.

+
Sources
+ +
+ Restrictions: + Public domain. NEISS data are produced by the U.S. Consumer Product Safety Commission and are generally not subject to copyright restrictions. +
+

Variables

data_agegroup_diagnosis.csv.gz
@@ -17927,7 +18322,7 @@
- data_agegroup_product_rate.csv.gz + data_agegroup_diagnosis_rate.csv.gz
@@ -17979,145 +18374,271 @@
- - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + @@ -18485,7 +19006,7 @@
- neiss_rate_chemicals + neiss_rate_amputation Chemicals injury rateAnnual ED injury visits whose primary product was chemicals per 100,000 U.S. population, by age and sex.Amputation injury rateAnnual ED injury visits with a primary diagnosis of amputation per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_child_nursery_equipment + neiss_rate_anoxia Child nursery equipment injury rateAnnual ED injury visits whose primary product was child nursery equipment per 100,000 U.S. population, by age and sex.Anoxia injury rateAnnual ED injury visits with a primary diagnosis of anoxia per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_general_household_appliances + neiss_rate_aspirated_object General household appliances injury rateAnnual ED injury visits whose primary product was general household appliances per 100,000 U.S. population, by age and sex.Aspirated object injury rateAnnual ED injury visits with a primary diagnosis of aspirated object per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_heating_cooling_ventilation + neiss_rate_avulsion Heating, cooling & ventilation injury rateAnnual ED injury visits whose primary product was heating, cooling & ventilation per 100,000 U.S. population, by age and sex.Avulsion injury rateAnnual ED injury visits with a primary diagnosis of avulsion per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_home_communication_entertainment_hobby + neiss_rate_burns_chemical Home communication, entertainment & hobby injury rateAnnual ED injury visits whose primary product was home communication, entertainment & hobby per 100,000 U.S. population, by age and sex.Chemical burns injury rateAnnual ED injury visits with a primary diagnosis of chemical burns per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_home_furnishings_fixtures + neiss_rate_burns_elec Home furnishings & fixtures injury rateAnnual ED injury visits whose primary product was home furnishings & fixtures per 100,000 U.S. population, by age and sex.Electrical burns injury rateAnnual ED injury visits with a primary diagnosis of electrical burns per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_home_structures_construction_materials + neiss_rate_burns_radiation Home structures & construction materials injury rateAnnual ED injury visits whose primary product was home structures & construction materials per 100,000 U.S. population, by age and sex.Radiation burns injury rateAnnual ED injury visits with a primary diagnosis of radiation burns per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_home_workshop_equipment_tools + neiss_rate_burns_scald Home workshop equipment & tools injury rateAnnual ED injury visits whose primary product was home workshop equipment & tools per 100,000 U.S. population, by age and sex.Scald burns injury rateAnnual ED injury visits with a primary diagnosis of scald burns per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_housewares + neiss_rate_burns_thermal Housewares injury rateAnnual ED injury visits whose primary product was housewares per 100,000 U.S. population, by age and sex.Thermal burns injury rateAnnual ED injury visits with a primary diagnosis of thermal burns per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_kitchen_appliances + neiss_rate_concussion Kitchen appliances injury rateAnnual ED injury visits whose primary product was kitchen appliances per 100,000 U.S. population, by age and sex.Concussion injury rateAnnual ED injury visits with a primary diagnosis of concussion per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_other_unspecified + neiss_rate_contusion_or_abrasion Other/unspecified product injury rateAnnual ED injury visits whose primary product was other/unspecified product per 100,000 U.S. population, by age and sex.Contusion or abrasion injury rateAnnual ED injury visits with a primary diagnosis of contusion or abrasion per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_packaging_containers + neiss_rate_crushing Packaging & containers injury rateAnnual ED injury visits whose primary product was packaging & containers per 100,000 U.S. population, by age and sex.Crushing injury injury rateAnnual ED injury visits with a primary diagnosis of crushing injury per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_personal_use_drugs_misc + neiss_rate_dental_injury Personal use, drugs & misc. injury rateAnnual ED injury visits whose primary product was personal use, drugs & misc. per 100,000 U.S. population, by age and sex.Dental injury injury rateAnnual ED injury visits with a primary diagnosis of dental injury per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_sports_recreation_activities + neiss_rate_dermat_or_conj Sports & recreation activities injury rateAnnual ED injury visits whose primary product was sports & recreation activities per 100,000 U.S. population, by age and sex.Dermatitis or conjunctivitis injury rateAnnual ED injury visits with a primary diagnosis of dermatitis or conjunctivitis per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_sports_recreation_equipment_toys + neiss_rate_dislocation Sports/recreation equipment & toys injury rateAnnual ED injury visits whose primary product was sports/recreation equipment & toys per 100,000 U.S. population, by age and sex.Dislocation injury rateAnnual ED injury visits with a primary diagnosis of dislocation per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_yard_garden_equipment + neiss_rate_electric_shock Yard & garden equipment injury rateAnnual ED injury visits whose primary product was yard & garden equipment per 100,000 U.S. population, by age and sex.Electric shock injury rateAnnual ED injury visits with a primary diagnosis of electric shock per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_foreign_body + Foreign body injury rateAnnual ED injury visits with a primary diagnosis of foreign body per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_fracture + Fracture injury rateAnnual ED injury visits with a primary diagnosis of fracture per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_hematoma + Hematoma injury rateAnnual ED injury visits with a primary diagnosis of hematoma per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_hemorrhage + Hemorrhage injury rateAnnual ED injury visits with a primary diagnosis of hemorrhage per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_ingested_object + Ingested object injury rateAnnual ED injury visits with a primary diagnosis of ingested object per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_inter_organ_injury + Internal organ injury injury rateAnnual ED injury visits with a primary diagnosis of internal organ injury per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_laceration + Laceration injury rateAnnual ED injury visits with a primary diagnosis of laceration per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_nerve_damage + Nerve damage injury rateAnnual ED injury visits with a primary diagnosis of nerve damage per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_other_or_not_stated + Other or not stated injury rateAnnual ED injury visits with a primary diagnosis of other or not stated per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_poisoning + Poisoning injury rateAnnual ED injury visits with a primary diagnosis of poisoning per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_puncture + Puncture injury rateAnnual ED injury visits with a primary diagnosis of puncture per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_strain_sprain + Strain or sprain injury rateAnnual ED injury visits with a primary diagnosis of strain or sprain per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_submersion + Submersion injury rateAnnual ED injury visits with a primary diagnosis of submersion per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_burns_not_spec + Burns (unspecified) injury rateAnnual ED injury visits with a primary diagnosis of burns (unspecified) per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- data_infant_diagnosis_rate.csv.gz + data_agegroup_product_rate.csv.gz
@@ -18537,271 +19058,145 @@
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + @@ -19421,7 +19816,7 @@
- neiss_rate_fracture - Fracture injury rateAnnual ED injury visits with a primary diagnosis of fracture per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_inter_organ_injury - Internal organ injury injury rateAnnual ED injury visits with a primary diagnosis of internal organ injury per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_laceration - Laceration injury rateAnnual ED injury visits with a primary diagnosis of laceration per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_other_or_not_stated - Other or not stated injury rateAnnual ED injury visits with a primary diagnosis of other or not stated per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_strain_sprain - Strain or sprain injury rateAnnual ED injury visits with a primary diagnosis of strain or sprain per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_anoxia - Anoxia injury rateAnnual ED injury visits with a primary diagnosis of anoxia per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_burns_thermal - Thermal burns injury rateAnnual ED injury visits with a primary diagnosis of thermal burns per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_contusion_or_abrasion - Contusion or abrasion injury rateAnnual ED injury visits with a primary diagnosis of contusion or abrasion per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_poisoning - Poisoning injury rateAnnual ED injury visits with a primary diagnosis of poisoning per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_aspirated_object - Aspirated object injury rateAnnual ED injury visits with a primary diagnosis of aspirated object per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_burns_chemical - Chemical burns injury rateAnnual ED injury visits with a primary diagnosis of chemical burns per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_burns_scald - Scald burns injury rateAnnual ED injury visits with a primary diagnosis of scald burns per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_concussion - Concussion injury rateAnnual ED injury visits with a primary diagnosis of concussion per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_dermat_or_conj - Dermatitis or conjunctivitis injury rateAnnual ED injury visits with a primary diagnosis of dermatitis or conjunctivitis per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
- neiss_rate_foreign_body + neiss_rate_chemicals Foreign body injury rateAnnual ED injury visits with a primary diagnosis of foreign body per 100,000 U.S. population, by age and sex.Chemicals injury rateAnnual ED injury visits whose primary product was chemicals per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_hematoma + neiss_rate_child_nursery_equipment Hematoma injury rateAnnual ED injury visits with a primary diagnosis of hematoma per 100,000 U.S. population, by age and sex.Child nursery equipment injury rateAnnual ED injury visits whose primary product was child nursery equipment per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_hemorrhage + neiss_rate_general_household_appliances Hemorrhage injury rateAnnual ED injury visits with a primary diagnosis of hemorrhage per 100,000 U.S. population, by age and sex.General household appliances injury rateAnnual ED injury visits whose primary product was general household appliances per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_ingested_object + neiss_rate_heating_cooling_ventilation Ingested object injury rateAnnual ED injury visits with a primary diagnosis of ingested object per 100,000 U.S. population, by age and sex.Heating, cooling & ventilation injury rateAnnual ED injury visits whose primary product was heating, cooling & ventilation per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_crushing + neiss_rate_home_communication_entertainment_hobby Crushing injury injury rateAnnual ED injury visits with a primary diagnosis of crushing injury per 100,000 U.S. population, by age and sex.Home communication, entertainment & hobby injury rateAnnual ED injury visits whose primary product was home communication, entertainment & hobby per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_nerve_damage + neiss_rate_home_furnishings_fixtures Nerve damage injury rateAnnual ED injury visits with a primary diagnosis of nerve damage per 100,000 U.S. population, by age and sex.Home furnishings & fixtures injury rateAnnual ED injury visits whose primary product was home furnishings & fixtures per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_submersion + neiss_rate_home_structures_construction_materials Submersion injury rateAnnual ED injury visits with a primary diagnosis of submersion per 100,000 U.S. population, by age and sex.Home structures & construction materials injury rateAnnual ED injury visits whose primary product was home structures & construction materials per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_dislocation + neiss_rate_home_workshop_equipment_tools Dislocation injury rateAnnual ED injury visits with a primary diagnosis of dislocation per 100,000 U.S. population, by age and sex.Home workshop equipment & tools injury rateAnnual ED injury visits whose primary product was home workshop equipment & tools per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_avulsion + neiss_rate_housewares Avulsion injury rateAnnual ED injury visits with a primary diagnosis of avulsion per 100,000 U.S. population, by age and sex.Housewares injury rateAnnual ED injury visits whose primary product was housewares per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_dental_injury + neiss_rate_kitchen_appliances Dental injury injury rateAnnual ED injury visits with a primary diagnosis of dental injury per 100,000 U.S. population, by age and sex.Kitchen appliances injury rateAnnual ED injury visits whose primary product was kitchen appliances per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_puncture + neiss_rate_other_unspecified Puncture injury rateAnnual ED injury visits with a primary diagnosis of puncture per 100,000 U.S. population, by age and sex.Other/unspecified product injury rateAnnual ED injury visits whose primary product was other/unspecified product per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_amputation + neiss_rate_packaging_containers Amputation injury rateAnnual ED injury visits with a primary diagnosis of amputation per 100,000 U.S. population, by age and sex.Packaging & containers injury rateAnnual ED injury visits whose primary product was packaging & containers per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_burns_not_spec + neiss_rate_personal_use_drugs_misc Burns (unspecified) injury rateAnnual ED injury visits with a primary diagnosis of burns (unspecified) per 100,000 U.S. population, by age and sex.Personal use, drugs & misc. injury rateAnnual ED injury visits whose primary product was personal use, drugs & misc. per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_electric_shock + neiss_rate_sports_recreation_activities Electric shock injury rateAnnual ED injury visits with a primary diagnosis of electric shock per 100,000 U.S. population, by age and sex.Sports & recreation activities injury rateAnnual ED injury visits whose primary product was sports & recreation activities per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_burns_elec + neiss_rate_sports_recreation_equipment_toys Electrical burns injury rateAnnual ED injury visits with a primary diagnosis of electrical burns per 100,000 U.S. population, by age and sex.Sports/recreation equipment & toys injury rateAnnual ED injury visits whose primary product was sports/recreation equipment & toys per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_burns_radiation + neiss_rate_yard_garden_equipment Radiation burns injury rateAnnual ED injury visits with a primary diagnosis of radiation burns per 100,000 U.S. population, by age and sex.Yard & garden equipment injury rateAnnual ED injury visits whose primary product was yard & garden equipment per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- data_infant_product_rate.csv.gz + data_infant_diagnosis_rate.csv.gz
@@ -19473,145 +19868,271 @@
- - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + @@ -19978,6 +20499,204 @@
- neiss_rate_home_furnishings_fixtures + neiss_rate_fracture Home furnishings & fixtures injury rateAnnual ED injury visits whose primary product was home furnishings & fixtures per 100,000 U.S. population, by age and sex.Fracture injury rateAnnual ED injury visits with a primary diagnosis of fracture per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_personal_use_drugs_misc + neiss_rate_inter_organ_injury Personal use, drugs & misc. injury rateAnnual ED injury visits whose primary product was personal use, drugs & misc. per 100,000 U.S. population, by age and sex.Internal organ injury injury rateAnnual ED injury visits with a primary diagnosis of internal organ injury per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_sports_recreation_activities + neiss_rate_laceration Sports & recreation activities injury rateAnnual ED injury visits whose primary product was sports & recreation activities per 100,000 U.S. population, by age and sex.Laceration injury rateAnnual ED injury visits with a primary diagnosis of laceration per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_child_nursery_equipment + neiss_rate_other_or_not_stated Child nursery equipment injury rateAnnual ED injury visits whose primary product was child nursery equipment per 100,000 U.S. population, by age and sex.Other or not stated injury rateAnnual ED injury visits with a primary diagnosis of other or not stated per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_housewares + neiss_rate_strain_sprain Housewares injury rateAnnual ED injury visits whose primary product was housewares per 100,000 U.S. population, by age and sex.Strain or sprain injury rateAnnual ED injury visits with a primary diagnosis of strain or sprain per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_sports_recreation_equipment_toys + neiss_rate_anoxia Sports/recreation equipment & toys injury rateAnnual ED injury visits whose primary product was sports/recreation equipment & toys per 100,000 U.S. population, by age and sex.Anoxia injury rateAnnual ED injury visits with a primary diagnosis of anoxia per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_chemicals + neiss_rate_burns_thermal Chemicals injury rateAnnual ED injury visits whose primary product was chemicals per 100,000 U.S. population, by age and sex.Thermal burns injury rateAnnual ED injury visits with a primary diagnosis of thermal burns per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_home_communication_entertainment_hobby + neiss_rate_contusion_or_abrasion Home communication, entertainment & hobby injury rateAnnual ED injury visits whose primary product was home communication, entertainment & hobby per 100,000 U.S. population, by age and sex.Contusion or abrasion injury rateAnnual ED injury visits with a primary diagnosis of contusion or abrasion per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_home_structures_construction_materials + neiss_rate_poisoning Home structures & construction materials injury rateAnnual ED injury visits whose primary product was home structures & construction materials per 100,000 U.S. population, by age and sex.Poisoning injury rateAnnual ED injury visits with a primary diagnosis of poisoning per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_home_workshop_equipment_tools + neiss_rate_aspirated_object Home workshop equipment & tools injury rateAnnual ED injury visits whose primary product was home workshop equipment & tools per 100,000 U.S. population, by age and sex.Aspirated object injury rateAnnual ED injury visits with a primary diagnosis of aspirated object per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_kitchen_appliances + neiss_rate_burns_chemical Kitchen appliances injury rateAnnual ED injury visits whose primary product was kitchen appliances per 100,000 U.S. population, by age and sex.Chemical burns injury rateAnnual ED injury visits with a primary diagnosis of chemical burns per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_packaging_containers + neiss_rate_burns_scald Packaging & containers injury rateAnnual ED injury visits whose primary product was packaging & containers per 100,000 U.S. population, by age and sex.Scald burns injury rateAnnual ED injury visits with a primary diagnosis of scald burns per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_heating_cooling_ventilation + neiss_rate_concussion Heating, cooling & ventilation injury rateAnnual ED injury visits whose primary product was heating, cooling & ventilation per 100,000 U.S. population, by age and sex.Concussion injury rateAnnual ED injury visits with a primary diagnosis of concussion per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_other_unspecified + neiss_rate_dermat_or_conj Other/unspecified product injury rateAnnual ED injury visits whose primary product was other/unspecified product per 100,000 U.S. population, by age and sex.Dermatitis or conjunctivitis injury rateAnnual ED injury visits with a primary diagnosis of dermatitis or conjunctivitis per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_yard_garden_equipment + neiss_rate_foreign_body Yard & garden equipment injury rateAnnual ED injury visits whose primary product was yard & garden equipment per 100,000 U.S. population, by age and sex.Foreign body injury rateAnnual ED injury visits with a primary diagnosis of foreign body per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
- neiss_rate_general_household_appliances + neiss_rate_hematoma General household appliances injury rateAnnual ED injury visits whose primary product was general household appliances per 100,000 U.S. population, by age and sex.Hematoma injury rateAnnual ED injury visits with a primary diagnosis of hematoma per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_hemorrhage + Hemorrhage injury rateAnnual ED injury visits with a primary diagnosis of hemorrhage per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_ingested_object + Ingested object injury rateAnnual ED injury visits with a primary diagnosis of ingested object per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_crushing + Crushing injury injury rateAnnual ED injury visits with a primary diagnosis of crushing injury per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_nerve_damage + Nerve damage injury rateAnnual ED injury visits with a primary diagnosis of nerve damage per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_submersion + Submersion injury rateAnnual ED injury visits with a primary diagnosis of submersion per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_dislocation + Dislocation injury rateAnnual ED injury visits with a primary diagnosis of dislocation per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_avulsion + Avulsion injury rateAnnual ED injury visits with a primary diagnosis of avulsion per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_dental_injury + Dental injury injury rateAnnual ED injury visits with a primary diagnosis of dental injury per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_puncture + Puncture injury rateAnnual ED injury visits with a primary diagnosis of puncture per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_amputation + Amputation injury rateAnnual ED injury visits with a primary diagnosis of amputation per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_burns_not_spec + Burns (unspecified) injury rateAnnual ED injury visits with a primary diagnosis of burns (unspecified) per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_electric_shock + Electric shock injury rateAnnual ED injury visits with a primary diagnosis of electric shock per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_burns_elec + Electrical burns injury rateAnnual ED injury visits with a primary diagnosis of electrical burns per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_burns_radiation + Radiation burns injury rateAnnual ED injury visits with a primary diagnosis of radiation burns per 100,000 U.S. population, by age and sex. Rate Injuries per 100,000 population
+
+ data_infant_product_rate.csv.gz +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VariableShort NameDescriptionTypeUnit
+ geography + GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
+ time + TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
+ age + AgePatient age: age in completed months (00-23 months) in the infant files; a standard age band in the age-group files.categoricalcategory
+ sex + SexPatient sex (Male, Female, Unknown).categoricalcategory
+ neiss_rate_home_furnishings_fixtures + Home furnishings & fixtures injury rateAnnual ED injury visits whose primary product was home furnishings & fixtures per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_personal_use_drugs_misc + Personal use, drugs & misc. injury rateAnnual ED injury visits whose primary product was personal use, drugs & misc. per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_sports_recreation_activities + Sports & recreation activities injury rateAnnual ED injury visits whose primary product was sports & recreation activities per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_child_nursery_equipment + Child nursery equipment injury rateAnnual ED injury visits whose primary product was child nursery equipment per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_housewares + Housewares injury rateAnnual ED injury visits whose primary product was housewares per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_sports_recreation_equipment_toys + Sports/recreation equipment & toys injury rateAnnual ED injury visits whose primary product was sports/recreation equipment & toys per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_chemicals + Chemicals injury rateAnnual ED injury visits whose primary product was chemicals per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_home_communication_entertainment_hobby + Home communication, entertainment & hobby injury rateAnnual ED injury visits whose primary product was home communication, entertainment & hobby per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_home_structures_construction_materials + Home structures & construction materials injury rateAnnual ED injury visits whose primary product was home structures & construction materials per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_home_workshop_equipment_tools + Home workshop equipment & tools injury rateAnnual ED injury visits whose primary product was home workshop equipment & tools per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_kitchen_appliances + Kitchen appliances injury rateAnnual ED injury visits whose primary product was kitchen appliances per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_packaging_containers + Packaging & containers injury rateAnnual ED injury visits whose primary product was packaging & containers per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_heating_cooling_ventilation + Heating, cooling & ventilation injury rateAnnual ED injury visits whose primary product was heating, cooling & ventilation per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_other_unspecified + Other/unspecified product injury rateAnnual ED injury visits whose primary product was other/unspecified product per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_yard_garden_equipment + Yard & garden equipment injury rateAnnual ED injury visits whose primary product was yard & garden equipment per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+ neiss_rate_general_household_appliances + General household appliances injury rateAnnual ED injury visits whose primary product was general household appliances per 100,000 U.S. population, by age and sex.RateInjuries per 100,000 population
+

Nhtsa Crash

@@ -19997,6 +20716,69 @@
Sources
Public domain. NHTSA data is generally not subject to copyright restrictions.

Variables

+
+ data.csv.gz +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VariableShort NameDescriptionTypeUnit
+ geography + GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
+ time + TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
+ nhtsa_fatalities + Motor vehicle fatalitiesAnnual count of persons killed in motor vehicle traffic crashes.CountDeaths
+ nhtsa_fatal_crashes + Fatal crashesAnnual count of motor vehicle crashes resulting in at least one fatality.CountCrashes
+ nhtsa_fatality_rate + Fatality rate (per 100k)Annual motor vehicle fatalities per 100,000 residents. Population denominator is 2021 Census.RateDeaths per 100,000
+
data_age_sex.csv.gz
@@ -20231,69 +21013,6 @@
-
- data.csv.gz -
-
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
VariableShort NameDescriptionTypeUnit
- geography - GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
- time - TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
- nhtsa_fatalities - Motor vehicle fatalitiesAnnual count of persons killed in motor vehicle traffic crashes.CountDeaths
- nhtsa_fatal_crashes - Fatal crashesAnnual count of motor vehicle crashes resulting in at least one fatality.CountCrashes
- nhtsa_fatality_rate - Fatality rate (per 100k)Annual motor vehicle fatalities per 100,000 residents. Population denominator is 2021 Census.RateDeaths per 100,000
-

NIS

@@ -20312,7 +21031,7 @@
Sources

Variables

- data_insurance.csv.gz + data.csv.gz
@@ -20328,31 +21047,22 @@
- - - - + + + + - - + + - - - - - - - - + - + - + - + + + + + + + + + + + + + + +
- geography + birth_year GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS codeBirth YearCalendar year the child was born.integeryear
- insurance + age Insurance StatusHealth insurance coverage status of the child.AgeAge group of surveyed children. categorical
- birth_year - Birth YearCalendar year the child was born.integeryear
vaccine @@ -20364,45 +21074,63 @@
- vax_uptake_insurance + vax_uptake_overall Insurance statusOverall Percent of survey respondents who received the indicated vaccine percent percent
- vax_uptake_insurance_lcl + vax_uptake_overall_lcl Insurance status lower 95% CIOverall lower 95% CI Percent of survey respondents who received the indicated vaccine percent percent
- vax_uptake_insurance_ucl + vax_uptake_overall_ucl Insurance status upper 95% CIOverall upper 95% CI Percent of survey respondents who received the indicated vaccine percent percent
- sample_size_insurance + sample_size_overall Insurance statusOverall Number of children surveyed for vaccination coverage estimates in the National Immunization Survey (NIS). percent percent
+ geography + GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
+ time + TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
- data_urban.csv.gz + data_insurance.csv.gz
@@ -20427,10 +21155,10 @@
- - + + @@ -20454,36 +21182,36 @@
- + - + - + - + @@ -20492,7 +21220,7 @@
- urban + insurance UrbanicityUrban or rural classification of residence.Insurance StatusHealth insurance coverage status of the child. categorical
- vax_uptake_urban + vax_uptake_insurance UrbanizationInsurance status Percent of survey respondents who received the indicated vaccine percent percent
- vax_uptake_urban_lcl + vax_uptake_insurance_lcl Urbanization lower 95% CIInsurance status lower 95% CI Percent of survey respondents who received the indicated vaccine percent percent
- vax_uptake_urban_ucl + vax_uptake_insurance_ucl Urbanization upper 95% CIInsurance status upper 95% CI Percent of survey respondents who received the indicated vaccine percent percent
- sample_size_urban + sample_size_insurance UrbanizationInsurance status Number of children surveyed for vaccination coverage estimates in the National Immunization Survey (NIS). percent percent
- data.csv.gz + data_urban.csv.gz
@@ -20508,22 +21236,31 @@
- - - - + + + + - - + + + + + + + + + - + - + - + - + - - - - - - - - - - - - - -
- birth_year + geography Birth YearCalendar year the child was born.integeryearGeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
- age + urban AgeAge group of surveyed children.UrbanicityUrban or rural classification of residence. categorical
+ birth_year + Birth YearCalendar year the child was born.integeryear
vaccine @@ -20535,58 +21272,40 @@
- vax_uptake_overall + vax_uptake_urban OverallUrbanization Percent of survey respondents who received the indicated vaccine percent percent
- vax_uptake_overall_lcl + vax_uptake_urban_lcl Overall lower 95% CIUrbanization lower 95% CI Percent of survey respondents who received the indicated vaccine percent percent
- vax_uptake_overall_ucl + vax_uptake_urban_ucl Overall upper 95% CIUrbanization upper 95% CI Percent of survey respondents who received the indicated vaccine percent percent
- sample_size_overall + sample_size_urban OverallUrbanization Number of children surveyed for vaccination coverage estimates in the National Immunization Survey (NIS). percent percent
- geography - GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
- time - TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
@@ -21860,122 +22579,6 @@
-
-

NREVSS

-

The National Respiratory and Enteric Virus Surveillance System (NREVSS) is a voluntary, laboratory-based surveillance system that monitors temporal and geographic trends for respiratory syncytial virus (RSV), human parainfluenza viruses, respiratory adenoviruses, human metapneumovirus, human coronaviruses, and rotavirus circulation in the United States. Participating laboratories report weekly to CDC on the number of tests performed and the number positive for each virus. NREVSS data are used to characterize seasonal patterns of these viruses and to help public health officials anticipate and prepare for outbreaks. Data are aggregated at the HHS regional and national levels. The system has been operational since 1987 and includes approximately 300 participating laboratories across the United States.

-
Sources
- -
- Restrictions: - Public domain. CDC data is generally not subject to copyright restrictions. -
-

Variables

-
- data.csv.gz -
-
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
VariableShort NameDescriptionTypeUnit
- source - SourceData sourcecategorical
- geography - GeographyFIPS code identifier (00 = national, 2-digit = state, 5-digit = county)identifierFIPS code
- time - TimeDate in MM-DD-YYYY format (Saturday for weekly data)datedate
- scaled_cases - Scale CasesNumber of positive tests per week divided by the highest number of positive tests for that regionscaled positive testsscaled number
- pcr_detections - PCR detectionsNumber of positive tests per week by HHS regionNumber of positive testsNumber
- epiyr - Epi_yearEpidemiological yearyearyear
- epiwk - Epi_weekEpidemiological weekyearyear
- week - weekCalendar weekweekweek
- year - yearCalendar yearyearyear
-
-

NSSP

This dataset provides the percentage of emergency department patient visits for the specified pathogen of all ED patient visits for the specified geographic part of the country that were observed for the given week from data submitted to the National Syndromic Surveillance Program (NSSP). Note that the reported sub-state trends are from Health Service Areas (HSA) and the data reported from the health care facilities located within the given HSA. Health Service Areas are regions of one or more counties that align to patterns of care seeking. The HSA level data are reported for each county in the HSA. Some states report state-level data but not county-level data. In these instances, PopHIVE maps the state-level data to the counties in that state so that all counties in the state share the same value. These data are made available by the CDC.

@@ -22446,7 +23049,7 @@
Sources

Variables

- data_exemptions.csv.gz + data.csv.gz
@@ -22536,7 +23139,7 @@
- data.csv.gz + data_exemptions.csv.gz
@@ -22643,7 +23246,7 @@
Sources

Variables

- data_county.csv.gz + data.csv.gz
@@ -22693,20 +23296,11 @@
- - - - - - -
Percent Percent
- is_state_estimate - is_state_estimate
- data_state.csv.gz + data_county.csv.gz
@@ -22756,11 +23350,20 @@
+ + + + + + +
Percent Percent
+ is_state_estimate + is_state_estimate
- data.csv.gz + data_state.csv.gz
@@ -22930,7 +23533,7 @@
Sources

Variables

- data_county.csv.gz + data.csv.gz
@@ -23002,7 +23605,7 @@
- data.csv.gz + data_county.csv.gz
@@ -23648,7 +24251,7 @@
Sources

Variables

- data_age_ethnicity.csv.gz + data_age.csv.gz
@@ -23689,15 +24292,6 @@
- - - - - - -
category
- race_ethnicity - Race/EthnicityRace/ethnicity categorycategory
pct_no_seatbelt @@ -25997,7 +26591,7 @@
- data_age_sex.csv.gz + data_age_ethnicity.csv.gz
@@ -26040,10 +26634,10 @@
- - + + @@ -28346,7 +28940,7 @@
- sex + race_ethnicity SexSex category (Male, Female, Overall)Race/EthnicityRace/ethnicity category category
- data_age.csv.gz + data_age_sex.csv.gz
@@ -28387,6 +28981,15 @@
+ + + + + + +
category
+ sex + SexSex category (Male, Female, Overall)category
pct_no_seatbelt @@ -33897,41 +34500,29 @@
-
-

Bundle: Injury Overdose

+
+

Bundle: Gas

- Combined output bundle. Dist files: 17 parquet file(s). + Combined output bundle. Dist files: 6 parquet file(s).

Data sources: - BRFSS - ; - CMS Mmd - ; - Epic Chronic - ; - Epic Injury - ; - Gtrends - ; - Medicaid Quality + Abcs Gas ; - NCHS Mortality - ; - Noaa Heat Risk + Epic Gas ; - Wisqars + NNDS

Output Files (dist/)

- county_opioid_by_source.parquet + abcs_gas.parquet
Source files: - - cms_mmd/standard/data_state_county_age.csv.gz + + abcs_gas/standard/data.csv.gz
@@ -33948,60 +34539,252 @@
- year + geography - Year - Calendar year + Geography + State name, or "United States" for the national total. + identifier + state name + + + + time + + Time + Period end date in YYYY-mm-dd (ISO 8601) format. date - year + date + + + + age + + Age Group + Age group category + category + + + + + sex + + Sex + Sex category (Male, Female, Overall) + category + + + + + race_ethnicity + + Race/Ethnicity + Race/ethnicity category + category + + + + + measure + + Measure + + +
+ + Values: + + rate_cases + rate_deaths + N_cases + N_deaths +
+ + + + + + + value + + Value + Value of the measure named in the `measure` column; rate per 100,000 or case/death count. + Mixed + cases per 100,000 or count + + + +
+
+ abcs_gas_emm.parquet +
+
+ + Source files: + + + abcs_gas/standard/data_emm.csv.gz + +
+
+ + + + + + + + + + - + - + + + + + + + + + + - - - + + + + + + +
VariableShort NameDescriptionTypeUnit
geography GeographyGeographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)State name, or "United States" for the national total. identifiername or FIPS codestate name
- opioid_rate + time + TimePeriod end date in YYYY-mm-dd (ISO 8601) format.datedate
+ measure + emm type measure + +
+ + Values: + + emm_pct_emm_1 + emm_pct_emm_11 + emm_pct_emm_12 + emm_pct_emm_28 + emm_pct_emm_43 + emm_pct_emm_49 + emm_pct_emm_59 + emm_pct_emm_60 + emm_pct_emm_77 + emm_pct_emm_81 + emm_pct_emm_82 + emm_pct_emm_83 + emm_pct_emm_89 + emm_pct_emm_91 + emm_pct_emm_92 + emm_pct_other + emm_count_number_of_isolates +
opioid_rate(source variable: cms_opioid_use_disorder_overarching)
- source + value Data sourceValuePercent of invasive GAS isolates of the emm type named in `measure`; or the isolate count.Mixedpercent or count
+
+
+ abcs_gas_resistance.parquet +
+
+ + Source files: + + + abcs_gas/standard/data_resistance.csv.gz + +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VariableShort NameDescriptionTypeUnit
+ geography + GeographyState name, or "United States" for the national total.identifierstate name
+ time + TimePeriod end date in YYYY-mm-dd (ISO 8601) format.datedate
+ measure + Resistance measure
Values: - Medicare FFS + pct_resistant_penicillin + pct_resistant_erythromycin + pct_resistant_clindamycin + pct_resistant_cefotaxime + pct_resistant_tetracycline + pct_resistant_vancomycin + n_isolates
+ value + ValuePercent of invasive GAS isolates non-susceptible to the antibiotic named in `measure`; or the isolate count.Mixedpercent or count
- deaths_cause_age_demographics.parquet + abcs_gas_syndromes.parquet
Source files: - - wisqars/standard/data.csv.gz + + abcs_gas/standard/data_syndromes.csv.gz
@@ -34018,84 +34801,199 @@
- year + geography - Year - Calendar year + Geography + State name, or "United States" for the national total. + identifier + state name + + + + time + + Time + Period end date in YYYY-mm-dd (ISO 8601) format. + date + date + + + + measure + + Clinical syndrome + + +
+ + Values: + + pct_syndrome_cellulitis + pct_syndrome_bacteremia_without_focus + pct_syndrome_pneumonia + pct_syndrome_necrotizing_fasciitis + pct_syndrome_strep_toxic_shock +
+ + + + + + + value + + Percent of cases + Percent of invasive GAS cases presenting with the syndrome named in `measure`. + Percent + Percent + + + +
+
+ epic_gas.parquet +
+
+ + Source files: + + + epic_gas/standard/data.csv.gz + +
+
+ + + + + + + + + + + + + + + + + + + + + + + - - + - - - + + + - - - - + + + + - - - - + + + + + + +
VariableShort NameDescriptionTypeUnit
+ geography + GeographyState name, or "United States" for the national total.identifierstate name
+ time + TimePeriod end date in YYYY-mm-dd (ISO 8601) format.date dateyear
age Age GroupAge group categoryEpic Cosmos age band; "Total" is the all-ages aggregate. category
- sex + measure SexSex category (Male, Female, Overall)categoryMeasure + +
+ + Values: + + n_strep_throat + pct_strep_throat + n_patients +
+
- race + value RaceRace category as reported by CDC WISQARS.categoryValueValue of the measure named in the `measure` column; unit depends on that measure.Mixedpatients or percent
- ethnicity + suppressed EthnicityEthnicity category (e.g., Hispanic, Non-Hispanic) as reported by CDC WISQARS.categorySuppressed1 if Epic suppressed the underlying cell and the value was imputed as 5; 0 otherwise.Binary0/1
+
+
+ nnds_stss.parquet +
+
+ + Source files: + + + nnds/standard/data.csv.gz + +
+
+ + + + + + + + + + - + - + - + + + + + + + + @@ -34105,17 +35003,105 @@
- - + + + + + + +
VariableShort NameDescriptionTypeUnit
geography GeographyGeographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)State name, or "United States" for the national total. identifiername or FIPS codestate name
- cause_of_death + time Cause of deathTimePeriod end date in YYYY-mm-dd (ISO 8601) format.datedate
+ measure + Measure
Values: - Drug poisoning - Non-drug poisoning - Firearm (unintentional) - Firearm (intentional) - Firearm (homicide) - Firearm (suicide) - Firearm (legal intervention) - Motor vehicle, traffic - Pedal cyclist (motor vehicle) - Pedestrian (motor vehicle traffic) - Fall - Drowning, including water transport - Exposure to smoke, fire, flame - Natural/environmental - Suffocation + stss_cases_weekly + stss_cases_cumulative
value value(source variable: bundle_injury_overdose/dist/deaths_cause_age.parquet|value)ValueSTSS case count; weekly-incident or cumulative year-to-date per the `measure` column.CountCases
+
+
+
+

Bundle: Injury Overdose

+

+ Combined output bundle. Dist files: 17 parquet file(s). +

+

+ Data sources: + BRFSS + ; + CMS Mmd + ; + Epic Chronic + ; + Epic Injury + ; + Gtrends + ; + Medicaid Quality + ; + NCHS Mortality + ; + Noaa Heat Risk + ; + Wisqars +

+

Output Files (dist/)

+
+ county_opioid_by_source.parquet +
+
+ + Source files: + + + cms_mmd/standard/data_state_county_age.csv.gz + +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + - - @@ -34224,6 +35210,135 @@
VariableShort NameDescriptionTypeUnit
+ year + YearCalendar yeardateyear
+ geography + GeographyGeographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)identifiername or FIPS code
+ opioid_rate + opioid_rate(source variable: cms_opioid_use_disorder_overarching)
- N + source + Data source + +
+ + Values: + + Medicare FFS +
N(source variable: bundle_injury_overdose/dist/deaths_cause_age.parquet|N)
+
+ deaths_cause_age_demographics.parquet +
+
+ + Source files: + + + wisqars/standard/data.csv.gz + +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
VariableShort NameDescriptionTypeUnit
+ year + YearCalendar yeardateyear
+ age + Age GroupAge group categorycategory
+ sex + SexSex category (Male, Female, Overall)category
+ race + RaceRace category as reported by CDC WISQARS.category
+ ethnicity + EthnicityEthnicity category (e.g., Hispanic, Non-Hispanic) as reported by CDC WISQARS.category
+ geography + GeographyGeographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)identifiername or FIPS code
+ cause_of_death + Cause of death + +
+ + Values: + + Drug poisoning + Non-drug poisoning + Firearm (unintentional) + Firearm (intentional) + Firearm (homicide) + Firearm (suicide) + Firearm (legal intervention) + Motor vehicle, traffic + Pedal cyclist (motor vehicle) + Pedestrian (motor vehicle traffic) + Fall + Drowning, including water transport + Exposure to smoke, fire, flame + Natural/environmental + Suffocation +
+
+ value + value(source variable: bundle_injury_overdose/dist/deaths_cause_age.parquet|value)
+ N + N(source variable: bundle_injury_overdose/dist/deaths_cause_age.parquet|N)
+
firearms_by_demographics.parquet
@@ -35015,7 +36130,7 @@
- overdose_by_geography_and_source_county.parquet + overdose_by_geography_and_source.parquet
@@ -35061,15 +36176,6 @@
identifier name or FIPS code - - - geography_fips - - County FIPS code - 5-digit county FIPS code accompanying the county name in the geography column. - identifier - FIPS code - date @@ -35113,16 +36219,34 @@
value - value - (source variable: bundle_injury_overdose/dist/overdose_by_geography_and_source.parquet|value) - - + Overdose measure + Overdose-related surveillance measure; units and definition depend on the source (see source column). + Mixed (rate or probability, depending on source) + Varies by source + + + + value_scale + + Overdose measure (scaled 0-1) + Value rescaled to 0-1 relative to the geography and source maximum. + Scaled + 0-1 + + + + suppressed + + Value suppressed flag + 1 if the underlying source value was suppressed (small count) and imputed, 0 otherwise. + Binary + Binary indicator
- overdose_by_geography_and_source_state_year.parquet + overdose_by_geography_and_source_county.parquet
@@ -35170,21 +36294,30 @@
- age + geography_fips - Age Group - Age group category - category - + County FIPS code + 5-digit county FIPS code accompanying the county name in the geography column. + identifier + FIPS code - year + date - Year - Calendar year + Date + Date (Saturday for weekly data) date - year + date + + + + age + + Age Group + Age group category + category + @@ -35220,7 +36353,7 @@
- overdose_by_geography_and_source.parquet + overdose_by_geography_and_source_state_year.parquet
@@ -35266,15 +36399,6 @@
identifier name or FIPS code - - - date - - Date - Date (Saturday for weekly data) - date - date - age @@ -35284,6 +36408,15 @@
category + + + year + + Year + Calendar year + date + year + source @@ -35309,28 +36442,10 @@
value - Overdose measure - Overdose-related surveillance measure; units and definition depend on the source (see source column). - Mixed (rate or probability, depending on source) - Varies by source - - - - value_scale - - Overdose measure (scaled 0-1) - Value rescaled to 0-1 relative to the geography and source maximum. - Scaled - 0-1 - - - - suppressed - - Value suppressed flag - 1 if the underlying source value was suppressed (small count) and imputed, 0 otherwise. - Binary - Binary indicator + value + (source variable: bundle_injury_overdose/dist/overdose_by_geography_and_source.parquet|value) + + @@ -37515,7 +38630,7 @@
- pneumococcus_by_geography_year.parquet + pneumococcus_by_geography.parquet
@@ -37582,20 +38697,11 @@
- - - value_smooth - - Pneumococcal IPD % (3-year smoothed) - 3-year rolling average of the percent of IPD cases caused by each pneumococcal serotype. - Percent - % -
- pneumococcus_by_geography.parquet + pneumococcus_by_geography_year.parquet
@@ -37662,6 +38768,15 @@
+ + + value_smooth + + Pneumococcal IPD % (3-year smoothed) + 3-year rolling average of the percent of IPD cases caused by each pneumococcal serotype. + Percent + % +
diff --git a/resources/data_manifest.json b/resources/data_manifest.json index 08970bbf3..a5e32382b 100644 --- a/resources/data_manifest.json +++ b/resources/data_manifest.json @@ -1,5 +1,5 @@ { - "generated": "2026-08-05T09:36:46Z", + "generated": "2026-08-05T16:08:17Z", "repository": "PopHIVE/Ingest", "github_raw_base": "https://raw.githubusercontent.com/PopHIVE/Ingest/main", "bundles": { @@ -1147,7 +1147,7 @@ { "name": "value_nis", "short_name": "MMR uptake (NIS, 35 months)", - "description": "Percent of 2021 birth cohort with ≥1 dose MMR by 35 months, from CDC NIS.", + "description": "Percent of 2021 birth cohort with 1 dose MMR by 35 months, from CDC NIS.", "measure_type": "Percent", "unit": "%", "levels": {} @@ -2331,64 +2331,29 @@ } ] }, - "bundle_injury_overdose": { - "name": "bundle_injury_overdose", - "display_name": "Bundle: Injury Overdose", + "bundle_gas": { + "name": "bundle_gas", + "display_name": "Bundle: Gas", "dist_files": [ { - "filename": "county_opioid_by_source.parquet", - "path": "data/bundle_injury_overdose/dist/county_opioid_by_source.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/county_opioid_by_source.parquet", + "filename": "abcs_gas.parquet", + "path": "data/bundle_gas/dist/abcs_gas.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_gas/dist/abcs_gas.parquet", "columns": [ - { - "name": "year", - "short_name": "Year", - "description": "Calendar year", - "measure_type": "date", - "unit": "year", - "levels": {} - }, { "name": "geography", "short_name": "Geography", - "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", + "description": "State name, or \"United States\" for the national total.", "measure_type": "identifier", - "unit": "name or FIPS code", + "unit": "state name", "levels": {} }, { - "name": "opioid_rate", - "short_name": "opioid_rate", - "description": "", - "measure_type": "", - "unit": "", - "levels": {} - }, - { - "name": "source", - "short_name": "Data source", - "description": "", - "measure_type": "", - "unit": "", - "levels": { - "Medicare FFS": { - "source_id": "cms_opioid_use_disorder_overarching" - } - } - } - ] - }, - { - "filename": "deaths_cause_age_demographics.parquet", - "path": "data/bundle_injury_overdose/dist/deaths_cause_age_demographics.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/deaths_cause_age_demographics.parquet", - "columns": [ - { - "name": "year", - "short_name": "Year", - "description": "Calendar year", + "name": "time", + "short_name": "Time", + "description": "Period end date in YYYY-mm-dd (ISO 8601) format.", "measure_type": "date", - "unit": "year", + "unit": "date", "levels": {} }, { @@ -2408,219 +2373,268 @@ "levels": {} }, { - "name": "race", - "short_name": "Race", - "description": "Race category as reported by CDC WISQARS.", + "name": "race_ethnicity", + "short_name": "Race/Ethnicity", + "description": "Race/ethnicity category", "measure_type": "category", "unit": "", "levels": {} }, { - "name": "ethnicity", - "short_name": "Ethnicity", - "description": "Ethnicity category (e.g., Hispanic, Non-Hispanic) as reported by CDC WISQARS.", - "measure_type": "category", + "name": "measure", + "short_name": "Measure", + "description": "", + "measure_type": "", "unit": "", - "levels": {} + "levels": { + "rate_cases": { + "source_id": "case_rate" + }, + "rate_deaths": { + "source_id": "death_rate" + }, + "N_cases": { + "source_id": "n_cases" + }, + "N_deaths": { + "source_id": "n_deaths" + } + } }, + { + "name": "value", + "short_name": "Value", + "description": "Value of the measure named in the `measure` column; rate per 100,000 or case/death count.", + "measure_type": "Mixed", + "unit": "cases per 100,000 or count", + "levels": {} + } + ] + }, + { + "filename": "abcs_gas_emm.parquet", + "path": "data/bundle_gas/dist/abcs_gas_emm.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_gas/dist/abcs_gas_emm.parquet", + "columns": [ { "name": "geography", "short_name": "Geography", - "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", + "description": "State name, or \"United States\" for the national total.", "measure_type": "identifier", - "unit": "name or FIPS code", + "unit": "state name", "levels": {} }, { - "name": "cause_of_death", - "short_name": "Cause of death", + "name": "time", + "short_name": "Time", + "description": "Period end date in YYYY-mm-dd (ISO 8601) format.", + "measure_type": "date", + "unit": "date", + "levels": {} + }, + { + "name": "measure", + "short_name": "emm type measure", "description": "", "measure_type": "", "unit": "", "levels": { - "Drug poisoning": { - "source_id": "wisqars_rate_drug_poisoning" + "emm_pct_emm_1": { + "source_id": "emm_type" }, - "Non-drug poisoning": { - "source_id": "wisqars_rate_non_drug_poisoning" + "emm_pct_emm_11": { + "source_id": "emm_type" }, - "Firearm (unintentional)": { - "source_id": "wisqars_rate_firearm_accident" + "emm_pct_emm_12": { + "source_id": "emm_type" }, - "Firearm (intentional)": { - "source_id": "wisqars_rate_firearm_intentional" + "emm_pct_emm_28": { + "source_id": "emm_type" }, - "Firearm (homicide)": { - "source_id": "wisqars_rate_firearm_homicide" + "emm_pct_emm_43": { + "source_id": "emm_type" }, - "Firearm (suicide)": { - "source_id": "wisqars_rate_firearm_suicide" + "emm_pct_emm_49": { + "source_id": "emm_type" }, - "Firearm (legal intervention)": { - "source_id": "wisqars_rate_firearm_legal_intervention" + "emm_pct_emm_59": { + "source_id": "emm_type" }, - "Motor vehicle, traffic": { - "source_id": "wisqars_rate_motor_vehicle_traffic" + "emm_pct_emm_60": { + "source_id": "emm_type" }, - "Pedal cyclist (motor vehicle)": { - "source_id": "wisqars_rate_pedal_cyclist_mv_traffic" + "emm_pct_emm_77": { + "source_id": "emm_type" }, - "Pedestrian (motor vehicle traffic)": { - "source_id": "wisqars_rate_pedestrian_mv_traffic" + "emm_pct_emm_81": { + "source_id": "emm_type" }, - "Fall": { - "source_id": "wisqars_rate_fall" + "emm_pct_emm_82": { + "source_id": "emm_type" }, - "Drowning, including water transport": { - "source_id": "wisqars_rate_drowning_includes_water_transport_" + "emm_pct_emm_83": { + "source_id": "emm_type" }, - "Exposure to smoke, fire, flame": { - "source_id": "wisqars_rate_fire_flame" + "emm_pct_emm_89": { + "source_id": "emm_type" }, - "Natural/environmental": { - "source_id": "wisqars_rate_natural_environmental" + "emm_pct_emm_91": { + "source_id": "emm_type" }, - "Suffocation": { - "source_id": "wisqars_rate_suffocation" + "emm_pct_emm_92": { + "source_id": "emm_type" + }, + "emm_pct_other": { + "source_id": "emm_type" + }, + "emm_count_number_of_isolates": { + "source_id": "n_isolates" } } }, { "name": "value", - "short_name": "value", - "description": "", - "measure_type": "", - "unit": "", - "levels": {} - }, - { - "name": "N", - "short_name": "N", - "description": "", - "measure_type": "", - "unit": "", + "short_name": "Value", + "description": "Percent of invasive GAS isolates of the emm type named in `measure`; or the isolate count.", + "measure_type": "Mixed", + "unit": "percent or count", "levels": {} } ] }, { - "filename": "deaths_cause_age.parquet", - "path": "data/bundle_injury_overdose/dist/deaths_cause_age.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/deaths_cause_age.parquet", + "filename": "abcs_gas_resistance.parquet", + "path": "data/bundle_gas/dist/abcs_gas_resistance.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_gas/dist/abcs_gas_resistance.parquet", "columns": [ { - "name": "year", - "short_name": "Year", - "description": "Calendar year", + "name": "geography", + "short_name": "Geography", + "description": "State name, or \"United States\" for the national total.", + "measure_type": "identifier", + "unit": "state name", + "levels": {} + }, + { + "name": "time", + "short_name": "Time", + "description": "Period end date in YYYY-mm-dd (ISO 8601) format.", "measure_type": "date", - "unit": "year", + "unit": "date", "levels": {} }, { - "name": "age", - "short_name": "Age Group", - "description": "Age group category", - "measure_type": "category", + "name": "measure", + "short_name": "Resistance measure", + "description": "", + "measure_type": "", "unit": "", - "levels": {} + "levels": { + "pct_resistant_penicillin": { + "source_id": "pct_resistant" + }, + "pct_resistant_erythromycin": { + "source_id": "pct_resistant" + }, + "pct_resistant_clindamycin": { + "source_id": "pct_resistant" + }, + "pct_resistant_cefotaxime": { + "source_id": "pct_resistant" + }, + "pct_resistant_tetracycline": { + "source_id": "pct_resistant" + }, + "pct_resistant_vancomycin": { + "source_id": "pct_resistant" + }, + "n_isolates": { + "source_id": "n_isolates" + } + } }, + { + "name": "value", + "short_name": "Value", + "description": "Percent of invasive GAS isolates non-susceptible to the antibiotic named in `measure`; or the isolate count.", + "measure_type": "Mixed", + "unit": "percent or count", + "levels": {} + } + ] + }, + { + "filename": "abcs_gas_syndromes.parquet", + "path": "data/bundle_gas/dist/abcs_gas_syndromes.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_gas/dist/abcs_gas_syndromes.parquet", + "columns": [ { "name": "geography", "short_name": "Geography", - "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", + "description": "State name, or \"United States\" for the national total.", "measure_type": "identifier", - "unit": "name or FIPS code", + "unit": "state name", "levels": {} }, { - "name": "cause_of_death", - "short_name": "Cause of death", + "name": "time", + "short_name": "Time", + "description": "Period end date in YYYY-mm-dd (ISO 8601) format.", + "measure_type": "date", + "unit": "date", + "levels": {} + }, + { + "name": "measure", + "short_name": "Clinical syndrome", "description": "", "measure_type": "", "unit": "", "levels": { - "Drug poisoning": { - "source_id": "wisqars_rate_drug_poisoning" - }, - "Non-drug poisoning": { - "source_id": "wisqars_rate_non_drug_poisoning" - }, - "Firearm (unintentional)": { - "source_id": "wisqars_rate_firearm_accident" - }, - "Firearm (intentional)": { - "source_id": "wisqars_rate_firearm_intentional" - }, - "Firearm (homicide)": { - "source_id": "wisqars_rate_firearm_homicide" - }, - "Firearm (suicide)": { - "source_id": "wisqars_rate_firearm_suicide" - }, - "Firearm (legal intervention)": { - "source_id": "wisqars_rate_firearm_legal_intervention" - }, - "Motor vehicle, traffic": { - "source_id": "wisqars_rate_motor_vehicle_traffic" - }, - "Pedal cyclist (motor vehicle)": { - "source_id": "wisqars_rate_pedal_cyclist_mv_traffic" - }, - "Pedestrian (motor vehicle traffic)": { - "source_id": "wisqars_rate_pedestrian_mv_traffic" - }, - "Fall": { - "source_id": "wisqars_rate_fall" + "pct_syndrome_cellulitis": { + "source_id": "syndrome" }, - "Drowning, including water transport": { - "source_id": "wisqars_rate_drowning_includes_water_transport_" + "pct_syndrome_bacteremia_without_focus": { + "source_id": "syndrome" }, - "Exposure to smoke, fire, flame": { - "source_id": "wisqars_rate_fire_flame" + "pct_syndrome_pneumonia": { + "source_id": "syndrome" }, - "Natural/environmental": { - "source_id": "wisqars_rate_natural_environmental" + "pct_syndrome_necrotizing_fasciitis": { + "source_id": "syndrome" }, - "Suffocation": { - "source_id": "wisqars_rate_suffocation" + "pct_syndrome_strep_toxic_shock": { + "source_id": "syndrome" } } }, { "name": "value", - "short_name": "Injury death rate", - "description": "Age-adjusted death rate per 100,000 population by injury cause.", - "measure_type": "Rate", - "unit": "Deaths per 100,000", - "levels": {} - }, - { - "name": "N", - "short_name": "Injury death count", - "description": "Count of injury deaths by cause of death and age group.", - "measure_type": "Count", - "unit": "Deaths", + "short_name": "Percent of cases", + "description": "Percent of invasive GAS cases presenting with the syndrome named in `measure`.", + "measure_type": "Percent", + "unit": "Percent", "levels": {} } ] }, { - "filename": "firearms_by_demographics.parquet", - "path": "data/bundle_injury_overdose/dist/firearms_by_demographics.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/firearms_by_demographics.parquet", + "filename": "epic_gas.parquet", + "path": "data/bundle_gas/dist/epic_gas.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_gas/dist/epic_gas.parquet", "columns": [ { "name": "geography", "short_name": "Geography", - "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", + "description": "State name, or \"United States\" for the national total.", "measure_type": "identifier", - "unit": "name or FIPS code", + "unit": "state name", "levels": {} }, { "name": "time", "short_name": "Time", - "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "description": "Period end date in YYYY-mm-dd (ISO 8601) format.", "measure_type": "date", "unit": "date", "levels": {} @@ -2628,80 +2642,121 @@ { "name": "age", "short_name": "Age Group", - "description": "Age group category", + "description": "Epic Cosmos age band; \"Total\" is the all-ages aggregate.", "measure_type": "category", "unit": "", "levels": {} }, { - "name": "sex", - "short_name": "Sex", - "description": "Sex category (Male, Female, Overall)", - "measure_type": "category", + "name": "measure", + "short_name": "Measure", + "description": "", + "measure_type": "", "unit": "", + "levels": { + "n_strep_throat": { + "source_id": "epic_n_strep_throat" + }, + "pct_strep_throat": { + "source_id": "epic_pct_strep_throat" + }, + "n_patients": { + "source_id": "epic_n_patients" + } + } + }, + { + "name": "value", + "short_name": "Value", + "description": "Value of the measure named in the `measure` column; unit depends on that measure.", + "measure_type": "Mixed", + "unit": "patients or percent", "levels": {} }, { - "name": "race", - "short_name": "Race", - "description": "Race category as reported by CDC WISQARS.", - "measure_type": "category", - "unit": "", + "name": "suppressed", + "short_name": "Suppressed", + "description": "1 if Epic suppressed the underlying cell and the value was imputed as 5; 0 otherwise.", + "measure_type": "Binary", + "unit": "0/1", + "levels": {} + } + ] + }, + { + "filename": "nnds_stss.parquet", + "path": "data/bundle_gas/dist/nnds_stss.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_gas/dist/nnds_stss.parquet", + "columns": [ + { + "name": "geography", + "short_name": "Geography", + "description": "State name, or \"United States\" for the national total.", + "measure_type": "identifier", + "unit": "state name", "levels": {} }, { - "name": "ethnicity", - "short_name": "Ethnicity", - "description": "Ethnicity category (e.g., Hispanic, Non-Hispanic) as reported by CDC WISQARS.", - "measure_type": "category", - "unit": "", + "name": "time", + "short_name": "Time", + "description": "Period end date in YYYY-mm-dd (ISO 8601) format.", + "measure_type": "date", + "unit": "date", "levels": {} }, { - "name": "source", - "short_name": "Firearm death intent", + "name": "measure", + "short_name": "Measure", "description": "", "measure_type": "", "unit": "", "levels": { - "wisqars_rate_firearm_intentional": { - "source_id": "wisqars_rate_firearm_intentional" - }, - "wisqars_rate_firearm_accident": { - "source_id": "wisqars_rate_firearm_accident" - }, - "wisqars_rate_firearm_homicide": { - "source_id": "wisqars_rate_firearm_homicide" - }, - "wisqars_rate_firearm_suicide": { - "source_id": "wisqars_rate_firearm_suicide" + "stss_cases_weekly": { + "short_name": "Strep TSS cases (weekly)", + "long_name": "Weekly incident cases of streptococcal toxic shock syndrome", + "short_description": "Newly reported STSS cases in the MMWR week.", + "long_description": "Incident cases of streptococcal toxic shock syndrome (STSS) newly reported in the MMWR week, derived by build.R as the week-over-week difference in the cumulative year-to-date count within each geography and MMWR year. This is the series to use for plotting trends. NNDSS occasionally revises earlier weeks downward, which produces a small number of negative increments (27 of 12,376 as of the current build); these are left as reported rather than clamped, and build.R logs the count.", + "measure_type": "Count", + "unit": "Cases", + "time_resolution": "Week", + "sources": [ + { + "id": "nnds" + } + ] }, - "wisqars_rate_firearm_legal_intervention": { - "source_id": "wisqars_rate_firearm_legal_intervention" + "stss_cases_cumulative": { + "source_id": "streptococcal_toxic_shock_syndrome" } } }, { "name": "value", - "short_name": "Firearm death rate", - "description": "Firearm death rate per 100,000 population by intent, age, sex, race, and ethnicity.", - "measure_type": "Rate", - "unit": "Deaths per 100,000", + "short_name": "Value", + "description": "STSS case count; weekly-incident or cumulative year-to-date per the `measure` column.", + "measure_type": "Count", + "unit": "Cases", "levels": {} } ] - }, + } + ] + }, + "bundle_injury_overdose": { + "name": "bundle_injury_overdose", + "display_name": "Bundle: Injury Overdose", + "dist_files": [ { - "filename": "firearms_by_geography_and_source_state_year.parquet", - "path": "data/bundle_injury_overdose/dist/firearms_by_geography_and_source_state_year.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/firearms_by_geography_and_source_state_year.parquet", + "filename": "county_opioid_by_source.parquet", + "path": "data/bundle_injury_overdose/dist/county_opioid_by_source.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/county_opioid_by_source.parquet", "columns": [ { - "name": "age", - "short_name": "Age Group", - "description": "Age group category", - "measure_type": "category", - "unit": "", + "name": "year", + "short_name": "Year", + "description": "Calendar year", + "measure_type": "date", + "unit": "year", "levels": {} }, { @@ -2712,33 +2767,33 @@ "unit": "name or FIPS code", "levels": {} }, + { + "name": "opioid_rate", + "short_name": "opioid_rate", + "description": "", + "measure_type": "", + "unit": "", + "levels": {} + }, { "name": "source", - "short_name": "Firearm measure / source", + "short_name": "Data source", "description": "", "measure_type": "", "unit": "", "levels": { - "CDC/WISQARS: Firearm (intentional)": { - "source_id": "wisqars_rate_firearm_intentional" - }, - "CDC/WISQARS: Firearm (unintentional)": { - "source_id": "wisqars_rate_firearm_accident" - }, - "CDC/WISQARS: Firearm (homicide)": { - "source_id": "wisqars_rate_firearm_homicide" - }, - "CDC/WISQARS: Firearm (suicide)": { - "source_id": "wisqars_rate_firearm_suicide" - }, - "CDC/WISQARS: Firearm (legal intervention)": { - "source_id": "wisqars_rate_firearm_legal_intervention" - }, - "Epic Cosmos": { - "source_id": "epic_rate_ed_firearm" + "Medicare FFS": { + "source_id": "cms_opioid_use_disorder_overarching" } } - }, + } + ] + }, + { + "filename": "deaths_cause_age.parquet", + "path": "data/bundle_injury_overdose/dist/deaths_cause_age.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/deaths_cause_age.parquet", + "columns": [ { "name": "year", "short_name": "Year", @@ -2748,251 +2803,222 @@ "levels": {} }, { - "name": "value", - "short_name": "value", - "description": "", - "measure_type": "", + "name": "age", + "short_name": "Age Group", + "description": "Age group category", + "measure_type": "category", "unit": "", "levels": {} }, { - "name": "epic_n_ed_firearm", - "short_name": "Firearm ED encounter count", - "description": "Count of firearm-related emergency department encounters from Epic Cosmos.", - "measure_type": "Count", - "unit": "Encounters", - "levels": {} - }, - { - "name": "suppressed_firearm", - "short_name": "Firearm value suppressed flag", - "description": "1 if the Epic Cosmos firearm ED value was suppressed (small count) and imputed, 0 otherwise.", - "measure_type": "Binary", - "unit": "Binary indicator", - "levels": {} - } - ] - }, - { - "filename": "firearms_geography_source.parquet", - "path": "data/bundle_injury_overdose/dist/firearms_geography_source.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/firearms_geography_source.parquet", - "columns": [ - { - "name": "time", - "short_name": "Time", - "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", - "measure_type": "date", - "unit": "date", + "name": "geography", + "short_name": "Geography", + "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", + "measure_type": "identifier", + "unit": "name or FIPS code", "levels": {} }, { - "name": "source", - "short_name": "Firearm measure / source", + "name": "cause_of_death", + "short_name": "Cause of death", "description": "", "measure_type": "", "unit": "", "levels": { - "gtrends_9mm": { - "source_id": "gtrends_9mm" + "Drug poisoning": { + "source_id": "wisqars_rate_drug_poisoning" }, - "gtrends_shotgun": { - "source_id": "gtrends_shotgun" + "Non-drug poisoning": { + "source_id": "wisqars_rate_non_drug_poisoning" }, - "Epic Cosmos": { - "source_id": "epic_rate_ed_firearm" + "Firearm (unintentional)": { + "source_id": "wisqars_rate_firearm_accident" }, - "wisqars_rate_firearm_intentional": { + "Firearm (intentional)": { "source_id": "wisqars_rate_firearm_intentional" }, - "wisqars_rate_firearm_accident": { - "source_id": "wisqars_rate_firearm_accident" - }, - "wisqars_rate_firearm_homicide": { + "Firearm (homicide)": { "source_id": "wisqars_rate_firearm_homicide" }, - "wisqars_rate_firearm_suicide": { + "Firearm (suicide)": { "source_id": "wisqars_rate_firearm_suicide" }, - "wisqars_rate_firearm_legal_intervention": { + "Firearm (legal intervention)": { "source_id": "wisqars_rate_firearm_legal_intervention" + }, + "Motor vehicle, traffic": { + "source_id": "wisqars_rate_motor_vehicle_traffic" + }, + "Pedal cyclist (motor vehicle)": { + "source_id": "wisqars_rate_pedal_cyclist_mv_traffic" + }, + "Pedestrian (motor vehicle traffic)": { + "source_id": "wisqars_rate_pedestrian_mv_traffic" + }, + "Fall": { + "source_id": "wisqars_rate_fall" + }, + "Drowning, including water transport": { + "source_id": "wisqars_rate_drowning_includes_water_transport_" + }, + "Exposure to smoke, fire, flame": { + "source_id": "wisqars_rate_fire_flame" + }, + "Natural/environmental": { + "source_id": "wisqars_rate_natural_environmental" + }, + "Suffocation": { + "source_id": "wisqars_rate_suffocation" } } }, { "name": "value", - "short_name": "Firearm-related measure", - "description": "Firearm-related measure; units depend on the source (see source column).", - "measure_type": "Mixed (rate or probability, depending on source)", - "unit": "Varies by source", - "levels": {} - }, - { - "name": "age", - "short_name": "Age Group", - "description": "Age group category", - "measure_type": "category", - "unit": "", + "short_name": "Injury death rate", + "description": "Age-adjusted death rate per 100,000 population by injury cause.", + "measure_type": "Rate", + "unit": "Deaths per 100,000", "levels": {} }, { - "name": "epic_n_ed_firearm", - "short_name": "Firearm ED encounter count", - "description": "Count of firearm-related emergency department encounters from Epic Cosmos.", + "name": "N", + "short_name": "Injury death count", + "description": "Count of injury deaths by cause of death and age group.", "measure_type": "Count", - "unit": "Encounters", - "levels": {} - }, - { - "name": "suppressed_firearm", - "short_name": "Firearm value suppressed flag", - "description": "1 if the Epic Cosmos firearm ED value was suppressed (small count) and imputed, 0 otherwise.", - "measure_type": "Binary", - "unit": "Binary indicator", - "levels": {} - }, - { - "name": "geography", - "short_name": "Geography", - "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", - "measure_type": "identifier", - "unit": "name or FIPS code", - "levels": {} - }, - { - "name": "state", - "short_name": "State abbreviation", - "description": "Two-letter USPS state abbreviation (e.g., CA, TX; US for national).", - "measure_type": "identifier", - "unit": "state abbreviation", + "unit": "Deaths", "levels": {} } ] }, { - "filename": "google_dma.parquet", - "path": "data/bundle_injury_overdose/dist/google_dma.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/google_dma.parquet", + "filename": "deaths_cause_age_demographics.parquet", + "path": "data/bundle_injury_overdose/dist/deaths_cause_age_demographics.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/deaths_cause_age_demographics.parquet", "columns": [ { - "name": "fips", - "short_name": "FIPS Code", - "description": "FIPS geographic identifier", - "measure_type": "identifier", - "unit": "FIPS code", - "levels": {} - }, - { - "name": "date", - "short_name": "Date", - "description": "Date (Saturday for weekly data)", + "name": "year", + "short_name": "Year", + "description": "Calendar year", "measure_type": "date", - "unit": "date", + "unit": "year", "levels": {} }, { - "name": "gtrends_narcan", - "short_name": "gtrends_narcan", - "description": "", - "measure_type": "", + "name": "age", + "short_name": "Age Group", + "description": "Age group category", + "measure_type": "category", "unit": "", "levels": {} }, { - "name": "gtrends_9mm", - "short_name": "gtrends_9mm", - "description": "", - "measure_type": "", + "name": "sex", + "short_name": "Sex", + "description": "Sex category (Male, Female, Overall)", + "measure_type": "category", "unit": "", "levels": {} }, { - "name": "gtrends_shotgun", - "short_name": "gtrends_shotgun", - "description": "", - "measure_type": "", + "name": "race", + "short_name": "Race", + "description": "Race category as reported by CDC WISQARS.", + "measure_type": "category", "unit": "", "levels": {} }, { - "name": "gtrends_heat_exhaustion", - "short_name": "gtrends_heat_exhaustion", - "description": "", - "measure_type": "", + "name": "ethnicity", + "short_name": "Ethnicity", + "description": "Ethnicity category (e.g., Hispanic, Non-Hispanic) as reported by CDC WISQARS.", + "measure_type": "category", "unit": "", "levels": {} - } - ] - }, - { - "filename": "heat_by_geography_and_source_state_year.parquet", - "path": "data/bundle_injury_overdose/dist/heat_by_geography_and_source_state_year.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/heat_by_geography_and_source_state_year.parquet", - "columns": [ + }, { - "name": "year", - "short_name": "Year", - "description": "Calendar year", - "measure_type": "date", - "unit": "year", + "name": "geography", + "short_name": "Geography", + "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", + "measure_type": "identifier", + "unit": "name or FIPS code", "levels": {} }, { - "name": "source", - "short_name": "Data source", + "name": "cause_of_death", + "short_name": "Cause of death", "description": "", "measure_type": "", "unit": "", "levels": { - "Google Health Trends: Heat Stroke": { - "source_id": "gtrends_heat+stroke" + "Drug poisoning": { + "source_id": "wisqars_rate_drug_poisoning" }, - "Google Health Trends: Heat Exhaustion": { - "source_id": "gtrends_heat+exhaustion" + "Non-drug poisoning": { + "source_id": "wisqars_rate_non_drug_poisoning" }, - "Epic Cosmos": { - "source_id": "epic_rate_ed_heat" + "Firearm (unintentional)": { + "source_id": "wisqars_rate_firearm_accident" + }, + "Firearm (intentional)": { + "source_id": "wisqars_rate_firearm_intentional" + }, + "Firearm (homicide)": { + "source_id": "wisqars_rate_firearm_homicide" + }, + "Firearm (suicide)": { + "source_id": "wisqars_rate_firearm_suicide" + }, + "Firearm (legal intervention)": { + "source_id": "wisqars_rate_firearm_legal_intervention" + }, + "Motor vehicle, traffic": { + "source_id": "wisqars_rate_motor_vehicle_traffic" + }, + "Pedal cyclist (motor vehicle)": { + "source_id": "wisqars_rate_pedal_cyclist_mv_traffic" + }, + "Pedestrian (motor vehicle traffic)": { + "source_id": "wisqars_rate_pedestrian_mv_traffic" + }, + "Fall": { + "source_id": "wisqars_rate_fall" + }, + "Drowning, including water transport": { + "source_id": "wisqars_rate_drowning_includes_water_transport_" + }, + "Exposure to smoke, fire, flame": { + "source_id": "wisqars_rate_fire_flame" + }, + "Natural/environmental": { + "source_id": "wisqars_rate_natural_environmental" + }, + "Suffocation": { + "source_id": "wisqars_rate_suffocation" } } }, - { - "name": "geography", - "short_name": "Geography", - "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", - "measure_type": "identifier", - "unit": "name or FIPS code", - "levels": {} - }, - { - "name": "age", - "short_name": "Age Group", - "description": "Age group category", - "measure_type": "category", - "unit": "", - "levels": {} - }, { "name": "value", - "short_name": "Heat-related measure", - "description": "Heat-related illness measure; units depend on the source (see source column).", - "measure_type": "Mixed (rate or probability, depending on source)", - "unit": "Varies by source", + "short_name": "value", + "description": "", + "measure_type": "", + "unit": "", "levels": {} }, { - "name": "suppressed_heat", - "short_name": "Heat value suppressed flag", - "description": "1 if the Epic Cosmos heat-related ED value was suppressed (small count) and imputed, 0 otherwise.", - "measure_type": "Binary", - "unit": "Binary indicator", + "name": "N", + "short_name": "N", + "description": "", + "measure_type": "", + "unit": "", "levels": {} } ] }, { - "filename": "heat_risk.parquet", - "path": "data/bundle_injury_overdose/dist/heat_risk.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/heat_risk.parquet", + "filename": "firearms_by_demographics.parquet", + "path": "data/bundle_injury_overdose/dist/firearms_by_demographics.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/firearms_by_demographics.parquet", "columns": [ { "name": "geography", @@ -3010,45 +3036,6 @@ "unit": "date", "levels": {} }, - { - "name": "value", - "short_name": "Heat risk score", - "description": "Mean daily heat risk score (0-4) aggregated to state (or county) level.", - "measure_type": "Index", - "unit": "Score (0-4)", - "levels": {} - }, - { - "name": "forecast_day", - "short_name": "Forecast day", - "description": "0 = historical archive (observed Day 1); 1-7 = number of days ahead in the current forecast.", - "measure_type": "Integer", - "unit": "Days", - "levels": {} - } - ] - }, - { - "filename": "medicaid_injury_overdose.parquet", - "path": "data/bundle_injury_overdose/dist/medicaid_injury_overdose.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/medicaid_injury_overdose.parquet", - "columns": [ - { - "name": "geography", - "short_name": "Geography", - "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", - "measure_type": "identifier", - "unit": "name or FIPS code", - "levels": {} - }, - { - "name": "year", - "short_name": "Year", - "description": "Calendar year", - "measure_type": "date", - "unit": "year", - "levels": {} - }, { "name": "age", "short_name": "Age Group", @@ -3066,59 +3053,68 @@ "levels": {} }, { - "name": "race_ethnicity", - "short_name": "Race/Ethnicity", - "description": "Race/ethnicity category", + "name": "race", + "short_name": "Race", + "description": "Race category as reported by CDC WISQARS.", "measure_type": "category", "unit": "", "levels": {} }, { - "name": "payer", - "short_name": "Payer", - "description": "Coverage/payer program the beneficiaries are enrolled in (e.g., Medicaid, CHIP).", + "name": "ethnicity", + "short_name": "Ethnicity", + "description": "Ethnicity category (e.g., Hispanic, Non-Hispanic) as reported by CDC WISQARS.", "measure_type": "category", "unit": "", "levels": {} }, - { - "name": "outcome_name", - "short_name": "Medicaid measure", - "description": "", - "measure_type": "", - "unit": "", - "levels": { - "Opioid Use Disorder": {}, - "Initiation and Engagement of Substance Use Treatment": {}, - "Follow-Up After ED Visit for Alcohol and Drug Abuse": {}, - "Concurrent Use of Opioids and Benzodiazepines": {} - } - }, { "name": "source", - "short_name": "Data source", + "short_name": "Firearm death intent", "description": "", "measure_type": "", "unit": "", "levels": { - "Medicaid": {} - } - }, - { - "name": "value", - "short_name": "Medicaid injury and overdose rate", - "description": "Percentage of Medicaid beneficiaries with injury and overdose related measures.", - "measure_type": "Percent", - "unit": "%", + "wisqars_rate_firearm_intentional": { + "source_id": "wisqars_rate_firearm_intentional" + }, + "wisqars_rate_firearm_accident": { + "source_id": "wisqars_rate_firearm_accident" + }, + "wisqars_rate_firearm_homicide": { + "source_id": "wisqars_rate_firearm_homicide" + }, + "wisqars_rate_firearm_suicide": { + "source_id": "wisqars_rate_firearm_suicide" + }, + "wisqars_rate_firearm_legal_intervention": { + "source_id": "wisqars_rate_firearm_legal_intervention" + } + } + }, + { + "name": "value", + "short_name": "Firearm death rate", + "description": "Firearm death rate per 100,000 population by intent, age, sex, race, and ethnicity.", + "measure_type": "Rate", + "unit": "Deaths per 100,000", "levels": {} } ] }, { - "filename": "overdose_by_demographics.parquet", - "path": "data/bundle_injury_overdose/dist/overdose_by_demographics.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/overdose_by_demographics.parquet", + "filename": "firearms_by_geography_and_source_state_year.parquet", + "path": "data/bundle_injury_overdose/dist/firearms_by_geography_and_source_state_year.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/firearms_by_geography_and_source_state_year.parquet", "columns": [ + { + "name": "age", + "short_name": "Age Group", + "description": "Age group category", + "measure_type": "category", + "unit": "", + "levels": {} + }, { "name": "geography", "short_name": "Geography", @@ -3128,37 +3124,71 @@ "levels": {} }, { - "name": "age", - "short_name": "Age Group", - "description": "Age group category", - "measure_type": "category", + "name": "source", + "short_name": "Firearm measure / source", + "description": "", + "measure_type": "", "unit": "", - "levels": {} + "levels": { + "CDC/WISQARS: Firearm (intentional)": { + "source_id": "wisqars_rate_firearm_intentional" + }, + "CDC/WISQARS: Firearm (unintentional)": { + "source_id": "wisqars_rate_firearm_accident" + }, + "CDC/WISQARS: Firearm (homicide)": { + "source_id": "wisqars_rate_firearm_homicide" + }, + "CDC/WISQARS: Firearm (suicide)": { + "source_id": "wisqars_rate_firearm_suicide" + }, + "CDC/WISQARS: Firearm (legal intervention)": { + "source_id": "wisqars_rate_firearm_legal_intervention" + }, + "Epic Cosmos": { + "source_id": "epic_rate_ed_firearm" + } + } }, { - "name": "sex", - "short_name": "Sex", - "description": "Sex category (Male, Female, Overall)", - "measure_type": "category", - "unit": "", + "name": "year", + "short_name": "Year", + "description": "Calendar year", + "measure_type": "date", + "unit": "year", "levels": {} }, { - "name": "race", - "short_name": "Race", - "description": "Race category as reported by CDC WISQARS.", - "measure_type": "category", + "name": "value", + "short_name": "value", + "description": "", + "measure_type": "", "unit": "", "levels": {} }, { - "name": "ethnicity", - "short_name": "Ethnicity", - "description": "Ethnicity category (e.g., Hispanic, Non-Hispanic) as reported by CDC WISQARS.", - "measure_type": "category", - "unit": "", + "name": "epic_n_ed_firearm", + "short_name": "Firearm ED encounter count", + "description": "Count of firearm-related emergency department encounters from Epic Cosmos.", + "measure_type": "Count", + "unit": "Encounters", "levels": {} }, + { + "name": "suppressed_firearm", + "short_name": "Firearm value suppressed flag", + "description": "1 if the Epic Cosmos firearm ED value was suppressed (small count) and imputed, 0 otherwise.", + "measure_type": "Binary", + "unit": "Binary indicator", + "levels": {} + } + ] + }, + { + "filename": "firearms_geography_source.parquet", + "path": "data/bundle_injury_overdose/dist/firearms_geography_source.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/firearms_geography_source.parquet", + "columns": [ { "name": "time", "short_name": "Time", @@ -3168,20 +3198,70 @@ "levels": {} }, { - "name": "wisqars_rate_drug_poisoning", - "short_name": "wisqars_rate_drug_poisoning", + "name": "source", + "short_name": "Firearm measure / source", "description": "", "measure_type": "", "unit": "", + "levels": { + "gtrends_9mm": { + "source_id": "gtrends_9mm" + }, + "gtrends_shotgun": { + "source_id": "gtrends_shotgun" + }, + "Epic Cosmos": { + "source_id": "epic_rate_ed_firearm" + }, + "wisqars_rate_firearm_intentional": { + "source_id": "wisqars_rate_firearm_intentional" + }, + "wisqars_rate_firearm_accident": { + "source_id": "wisqars_rate_firearm_accident" + }, + "wisqars_rate_firearm_homicide": { + "source_id": "wisqars_rate_firearm_homicide" + }, + "wisqars_rate_firearm_suicide": { + "source_id": "wisqars_rate_firearm_suicide" + }, + "wisqars_rate_firearm_legal_intervention": { + "source_id": "wisqars_rate_firearm_legal_intervention" + } + } + }, + { + "name": "value", + "short_name": "Firearm-related measure", + "description": "Firearm-related measure; units depend on the source (see source column).", + "measure_type": "Mixed (rate or probability, depending on source)", + "unit": "Varies by source", + "levels": {} + }, + { + "name": "age", + "short_name": "Age Group", + "description": "Age group category", + "measure_type": "category", + "unit": "", "levels": {} - } - ] - }, - { - "filename": "overdose_by_geography_and_source_county.parquet", - "path": "data/bundle_injury_overdose/dist/overdose_by_geography_and_source_county.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/overdose_by_geography_and_source_county.parquet", - "columns": [ + }, + { + "name": "epic_n_ed_firearm", + "short_name": "Firearm ED encounter count", + "description": "Count of firearm-related emergency department encounters from Epic Cosmos.", + "measure_type": "Count", + "unit": "Encounters", + "levels": {} + }, + { + "name": "suppressed_firearm", + "short_name": "Firearm value suppressed flag", + "description": "1 if the Epic Cosmos firearm ED value was suppressed (small count) and imputed, 0 otherwise.", + "measure_type": "Binary", + "unit": "Binary indicator", + "levels": {} + }, { "name": "geography", "short_name": "Geography", @@ -3191,9 +3271,24 @@ "levels": {} }, { - "name": "geography_fips", - "short_name": "County FIPS code", - "description": "5-digit county FIPS code accompanying the county name in the geography column.", + "name": "state", + "short_name": "State abbreviation", + "description": "Two-letter USPS state abbreviation (e.g., CA, TX; US for national).", + "measure_type": "identifier", + "unit": "state abbreviation", + "levels": {} + } + ] + }, + { + "filename": "google_dma.parquet", + "path": "data/bundle_injury_overdose/dist/google_dma.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/google_dma.parquet", + "columns": [ + { + "name": "fips", + "short_name": "FIPS Code", + "description": "FIPS geographic identifier", "measure_type": "identifier", "unit": "FIPS code", "levels": {} @@ -3207,40 +3302,32 @@ "levels": {} }, { - "name": "age", - "short_name": "Age Group", - "description": "Age group category", - "measure_type": "category", + "name": "gtrends_narcan", + "short_name": "gtrends_narcan", + "description": "", + "measure_type": "", "unit": "", "levels": {} }, { - "name": "source", - "short_name": "Data source", + "name": "gtrends_9mm", + "short_name": "gtrends_9mm", "description": "", "measure_type": "", "unit": "", - "levels": { - "CDC/NCHS": { - "source_id": "n_deaths_overdose" - }, - "Google Health Trends": { - "source_id": "gtrends_narcan" - }, - "CDC/WISQARS": { - "source_id": "wisqars_rate_drug_poisoning" - }, - "Epic Cosmos": { - "source_id": "epic_rate_ed_opioid" - }, - "Medicare FFS": { - "source_id": "cms_opioid_use_disorder_overarching" - } - } + "levels": {} }, { - "name": "value", - "short_name": "value", + "name": "gtrends_shotgun", + "short_name": "gtrends_shotgun", + "description": "", + "measure_type": "", + "unit": "", + "levels": {} + }, + { + "name": "gtrends_heat_exhaustion", + "short_name": "gtrends_heat_exhaustion", "description": "", "measure_type": "", "unit": "", @@ -3249,16 +3336,42 @@ ] }, { - "filename": "overdose_by_geography_and_source_state_year.parquet", - "path": "data/bundle_injury_overdose/dist/overdose_by_geography_and_source_state_year.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/overdose_by_geography_and_source_state_year.parquet", + "filename": "heat_by_geography_and_source_state_year.parquet", + "path": "data/bundle_injury_overdose/dist/heat_by_geography_and_source_state_year.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/heat_by_geography_and_source_state_year.parquet", "columns": [ { - "name": "geography", - "short_name": "Geography", - "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", - "measure_type": "identifier", - "unit": "name or FIPS code", + "name": "year", + "short_name": "Year", + "description": "Calendar year", + "measure_type": "date", + "unit": "year", + "levels": {} + }, + { + "name": "source", + "short_name": "Data source", + "description": "", + "measure_type": "", + "unit": "", + "levels": { + "Google Health Trends: Heat Stroke": { + "source_id": "gtrends_heat+stroke" + }, + "Google Health Trends: Heat Exhaustion": { + "source_id": "gtrends_heat+exhaustion" + }, + "Epic Cosmos": { + "source_id": "epic_rate_ed_heat" + } + } + }, + { + "name": "geography", + "short_name": "Geography", + "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", + "measure_type": "identifier", + "unit": "name or FIPS code", "levels": {} }, { @@ -3269,6 +3382,76 @@ "unit": "", "levels": {} }, + { + "name": "value", + "short_name": "Heat-related measure", + "description": "Heat-related illness measure; units depend on the source (see source column).", + "measure_type": "Mixed (rate or probability, depending on source)", + "unit": "Varies by source", + "levels": {} + }, + { + "name": "suppressed_heat", + "short_name": "Heat value suppressed flag", + "description": "1 if the Epic Cosmos heat-related ED value was suppressed (small count) and imputed, 0 otherwise.", + "measure_type": "Binary", + "unit": "Binary indicator", + "levels": {} + } + ] + }, + { + "filename": "heat_risk.parquet", + "path": "data/bundle_injury_overdose/dist/heat_risk.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/heat_risk.parquet", + "columns": [ + { + "name": "geography", + "short_name": "Geography", + "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", + "measure_type": "identifier", + "unit": "name or FIPS code", + "levels": {} + }, + { + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date", + "levels": {} + }, + { + "name": "value", + "short_name": "Heat risk score", + "description": "Mean daily heat risk score (0-4) aggregated to state (or county) level.", + "measure_type": "Index", + "unit": "Score (0-4)", + "levels": {} + }, + { + "name": "forecast_day", + "short_name": "Forecast day", + "description": "0 = historical archive (observed Day 1); 1-7 = number of days ahead in the current forecast.", + "measure_type": "Integer", + "unit": "Days", + "levels": {} + } + ] + }, + { + "filename": "medicaid_injury_overdose.parquet", + "path": "data/bundle_injury_overdose/dist/medicaid_injury_overdose.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/medicaid_injury_overdose.parquet", + "columns": [ + { + "name": "geography", + "short_name": "Geography", + "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", + "measure_type": "identifier", + "unit": "name or FIPS code", + "levels": {} + }, { "name": "year", "short_name": "Year", @@ -3277,6 +3460,51 @@ "unit": "year", "levels": {} }, + { + "name": "age", + "short_name": "Age Group", + "description": "Age group category", + "measure_type": "category", + "unit": "", + "levels": {} + }, + { + "name": "sex", + "short_name": "Sex", + "description": "Sex category (Male, Female, Overall)", + "measure_type": "category", + "unit": "", + "levels": {} + }, + { + "name": "race_ethnicity", + "short_name": "Race/Ethnicity", + "description": "Race/ethnicity category", + "measure_type": "category", + "unit": "", + "levels": {} + }, + { + "name": "payer", + "short_name": "Payer", + "description": "Coverage/payer program the beneficiaries are enrolled in (e.g., Medicaid, CHIP).", + "measure_type": "category", + "unit": "", + "levels": {} + }, + { + "name": "outcome_name", + "short_name": "Medicaid measure", + "description": "", + "measure_type": "", + "unit": "", + "levels": { + "Opioid Use Disorder": {}, + "Initiation and Engagement of Substance Use Treatment": {}, + "Follow-Up After ED Visit for Alcohol and Drug Abuse": {}, + "Concurrent Use of Opioids and Benzodiazepines": {} + } + }, { "name": "source", "short_name": "Data source", @@ -3284,26 +3512,75 @@ "measure_type": "", "unit": "", "levels": { - "CDC/NCHS": { - "source_id": "n_deaths_overdose" - }, - "Google Health Trends": { - "source_id": "gtrends_narcan" - }, - "CDC/WISQARS": { - "source_id": "wisqars_rate_drug_poisoning" - }, - "Epic Cosmos": { - "source_id": "epic_rate_ed_opioid" - }, - "Medicare FFS": { - "source_id": "cms_opioid_use_disorder_overarching" - } + "Medicaid": {} } }, { "name": "value", - "short_name": "value", + "short_name": "Medicaid injury and overdose rate", + "description": "Percentage of Medicaid beneficiaries with injury and overdose related measures.", + "measure_type": "Percent", + "unit": "%", + "levels": {} + } + ] + }, + { + "filename": "overdose_by_demographics.parquet", + "path": "data/bundle_injury_overdose/dist/overdose_by_demographics.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/overdose_by_demographics.parquet", + "columns": [ + { + "name": "geography", + "short_name": "Geography", + "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", + "measure_type": "identifier", + "unit": "name or FIPS code", + "levels": {} + }, + { + "name": "age", + "short_name": "Age Group", + "description": "Age group category", + "measure_type": "category", + "unit": "", + "levels": {} + }, + { + "name": "sex", + "short_name": "Sex", + "description": "Sex category (Male, Female, Overall)", + "measure_type": "category", + "unit": "", + "levels": {} + }, + { + "name": "race", + "short_name": "Race", + "description": "Race category as reported by CDC WISQARS.", + "measure_type": "category", + "unit": "", + "levels": {} + }, + { + "name": "ethnicity", + "short_name": "Ethnicity", + "description": "Ethnicity category (e.g., Hispanic, Non-Hispanic) as reported by CDC WISQARS.", + "measure_type": "category", + "unit": "", + "levels": {} + }, + { + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date", + "levels": {} + }, + { + "name": "wisqars_rate_drug_poisoning", + "short_name": "wisqars_rate_drug_poisoning", "description": "", "measure_type": "", "unit": "", @@ -3391,9 +3668,9 @@ ] }, { - "filename": "overdose_deaths_county.parquet", - "path": "data/bundle_injury_overdose/dist/overdose_deaths_county.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/overdose_deaths_county.parquet", + "filename": "overdose_by_geography_and_source_county.parquet", + "path": "data/bundle_injury_overdose/dist/overdose_by_geography_and_source_county.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/overdose_by_geography_and_source_county.parquet", "columns": [ { "name": "geography", @@ -3404,23 +3681,157 @@ "levels": {} }, { - "name": "time", - "short_name": "Time", - "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "name": "geography_fips", + "short_name": "County FIPS code", + "description": "5-digit county FIPS code accompanying the county name in the geography column.", + "measure_type": "identifier", + "unit": "FIPS code", + "levels": {} + }, + { + "name": "date", + "short_name": "Date", + "description": "Date (Saturday for weekly data)", "measure_type": "date", "unit": "date", "levels": {} }, { - "name": "n_deaths_overdose", - "short_name": "n_deaths_overdose", - "description": "", - "measure_type": "", + "name": "age", + "short_name": "Age Group", + "description": "Age group category", + "measure_type": "category", "unit": "", "levels": {} }, { - "name": "rate_deaths_overdose", + "name": "source", + "short_name": "Data source", + "description": "", + "measure_type": "", + "unit": "", + "levels": { + "CDC/NCHS": { + "source_id": "n_deaths_overdose" + }, + "Google Health Trends": { + "source_id": "gtrends_narcan" + }, + "CDC/WISQARS": { + "source_id": "wisqars_rate_drug_poisoning" + }, + "Epic Cosmos": { + "source_id": "epic_rate_ed_opioid" + }, + "Medicare FFS": { + "source_id": "cms_opioid_use_disorder_overarching" + } + } + }, + { + "name": "value", + "short_name": "value", + "description": "", + "measure_type": "", + "unit": "", + "levels": {} + } + ] + }, + { + "filename": "overdose_by_geography_and_source_state_year.parquet", + "path": "data/bundle_injury_overdose/dist/overdose_by_geography_and_source_state_year.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/overdose_by_geography_and_source_state_year.parquet", + "columns": [ + { + "name": "geography", + "short_name": "Geography", + "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", + "measure_type": "identifier", + "unit": "name or FIPS code", + "levels": {} + }, + { + "name": "age", + "short_name": "Age Group", + "description": "Age group category", + "measure_type": "category", + "unit": "", + "levels": {} + }, + { + "name": "year", + "short_name": "Year", + "description": "Calendar year", + "measure_type": "date", + "unit": "year", + "levels": {} + }, + { + "name": "source", + "short_name": "Data source", + "description": "", + "measure_type": "", + "unit": "", + "levels": { + "CDC/NCHS": { + "source_id": "n_deaths_overdose" + }, + "Google Health Trends": { + "source_id": "gtrends_narcan" + }, + "CDC/WISQARS": { + "source_id": "wisqars_rate_drug_poisoning" + }, + "Epic Cosmos": { + "source_id": "epic_rate_ed_opioid" + }, + "Medicare FFS": { + "source_id": "cms_opioid_use_disorder_overarching" + } + } + }, + { + "name": "value", + "short_name": "value", + "description": "", + "measure_type": "", + "unit": "", + "levels": {} + } + ] + }, + { + "filename": "overdose_deaths_county.parquet", + "path": "data/bundle_injury_overdose/dist/overdose_deaths_county.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_injury_overdose/dist/overdose_deaths_county.parquet", + "columns": [ + { + "name": "geography", + "short_name": "Geography", + "description": "Geographic area name (state or country name for state/national files; 5-digit FIPS code for county-level files)", + "measure_type": "identifier", + "unit": "name or FIPS code", + "levels": {} + }, + { + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date", + "levels": {} + }, + { + "name": "n_deaths_overdose", + "short_name": "n_deaths_overdose", + "description": "", + "measure_type": "", + "unit": "", + "levels": {} + }, + { + "name": "rate_deaths_overdose", "short_name": "rate_deaths_overdose", "description": "", "measure_type": "", @@ -3535,14 +3946,14 @@ "levels": { "birth_rate": { "id": "bundle_maternal_health/dist/maternal_county.parquet|measure=birth_rate", - "short_name": "Birth rate (women 15–50)", - "long_name": "Birth Rate Among Women Aged 15–50", + "short_name": "Birth rate (women 1550)", + "long_name": "Birth Rate Among Women Aged 1550", "category": "maternal", - "short_description": "Share of women aged 15–50 who gave birth in the past 12 months.", - "long_description": "Proportion of women aged 15–50 years who gave birth in the past 12 months, derived from ACS Table B13002. Used as an approximation of the general fertility rate.", - "statement": "In {location}, {value} of women aged 15–50 gave birth in the past year.", + "short_description": "Share of women aged 1550 who gave birth in the past 12 months.", + "long_description": "Proportion of women aged 1550 years who gave birth in the past 12 months, derived from ACS Table B13002. Used as an approximation of the general fertility rate.", + "statement": "In {location}, {value} of women aged 1550 gave birth in the past year.", "measure_type": "Percent", - "unit": "Proportion (0–1)", + "unit": "Proportion (01)", "time_resolution": "Year", "sources": [ { @@ -3627,7 +4038,7 @@ "long_description": "Percentage of women who reported smoking during pregnancy, from the National Center for Health Statistics (NCHS) Natality files. Coverage is limited; not all states/counties report this measure in every release year.", "statement": "In {location}, {value} of women smoked during pregnancy.", "measure_type": "Percent", - "unit": "Proportion (0–1)", + "unit": "Proportion (01)", "time_resolution": "Year", "sources": [ { @@ -3644,7 +4055,7 @@ "long_description": "Percentage of infants who were ever breastfed. Coverage is sparse; reported for only a small number of state/county-years in the County Health Rankings data.", "statement": "In {location}, {value} of infants were ever breastfed.", "measure_type": "Percent", - "unit": "Proportion (0–1)", + "unit": "Proportion (01)", "time_resolution": "Year", "sources": [ { @@ -3767,14 +4178,14 @@ "levels": { "birth_rate": { "id": "bundle_maternal_health/dist/maternal_state.parquet|measure=birth_rate", - "short_name": "Birth rate (women 15–50)", - "long_name": "Birth Rate Among Women Aged 15–50", + "short_name": "Birth rate (women 1550)", + "long_name": "Birth Rate Among Women Aged 1550", "category": "maternal", - "short_description": "Share of women aged 15–50 who gave birth in the past 12 months.", - "long_description": "Proportion of women aged 15–50 years who gave birth in the past 12 months, derived from ACS Table B13002. Used as an approximation of the general fertility rate.", - "statement": "In {location}, {value} of women aged 15–50 gave birth in the past year.", + "short_description": "Share of women aged 1550 who gave birth in the past 12 months.", + "long_description": "Proportion of women aged 1550 years who gave birth in the past 12 months, derived from ACS Table B13002. Used as an approximation of the general fertility rate.", + "statement": "In {location}, {value} of women aged 1550 gave birth in the past year.", "measure_type": "Percent", - "unit": "Proportion (0–1)", + "unit": "Proportion (01)", "time_resolution": "Year", "sources": [ { @@ -3859,7 +4270,7 @@ "long_description": "Percentage of women who reported smoking during pregnancy, from the National Center for Health Statistics (NCHS) Natality files. Coverage is limited; not all states/counties report this measure in every release year.", "statement": "In {location}, {value} of women smoked during pregnancy.", "measure_type": "Percent", - "unit": "Proportion (0–1)", + "unit": "Proportion (01)", "time_resolution": "Year", "sources": [ { @@ -3876,7 +4287,7 @@ "long_description": "Percentage of infants who were ever breastfed. Coverage is sparse; reported for only a small number of state/county-years in the County Health Rankings data.", "statement": "In {location}, {value} of infants were ever breastfed.", "measure_type": "Percent", - "unit": "Proportion (0–1)", + "unit": "Proportion (01)", "time_resolution": "Year", "sources": [ { @@ -3887,10 +4298,10 @@ "medicaid_prenatal_postpartum_care_adult": { "id": "bundle_maternal_health/dist/maternal_state.parquet|measure=medicaid_prenatal_postpartum_care_adult", "short_name": "Prenatal & Postpartum Care (Adult)", - "long_name": "Prenatal and Postpartum Care – Adults (Medicaid)", + "long_name": "Prenatal and Postpartum Care Adults (Medicaid)", "category": "maternal", "short_description": "Percent of adult women (Medicaid) who received timely prenatal and postpartum care.", - "long_description": "Adult Core Set measure (PPC). Percentage of women aged 21–44 enrolled in Medicaid who had a live birth and received a prenatal care visit in the first trimester and a postpartum visit within 21–56 days of delivery. State-level, Medicaid payer.", + "long_description": "Adult Core Set measure (PPC). Percentage of women aged 2144 enrolled in Medicaid who had a live birth and received a prenatal care visit in the first trimester and a postpartum visit within 2156 days of delivery. State-level, Medicaid payer.", "statement": "In {location}, {value}% of adult women received timely prenatal and postpartum care.", "measure_type": "Percent", "unit": "Percent", @@ -3904,10 +4315,10 @@ "medicaid_prenatal_postpartum_care_child": { "id": "bundle_maternal_health/dist/maternal_state.parquet|measure=medicaid_prenatal_postpartum_care_child", "short_name": "Prenatal & Postpartum Care (Adolescent)", - "long_name": "Prenatal and Postpartum Care – Adolescents (Medicaid)", + "long_name": "Prenatal and Postpartum Care Adolescents (Medicaid)", "category": "maternal", "short_description": "Percent of adolescent females (Medicaid) who received timely prenatal and postpartum care.", - "long_description": "Child Core Set measure (PPC). Percentage of adolescent females aged 15–20 enrolled in Medicaid who had a live birth and received a prenatal care visit in the first trimester and a postpartum visit within 21–56 days of delivery. State-level, Medicaid payer.", + "long_description": "Child Core Set measure (PPC). Percentage of adolescent females aged 1520 enrolled in Medicaid who had a live birth and received a prenatal care visit in the first trimester and a postpartum visit within 2156 days of delivery. State-level, Medicaid payer.", "statement": "In {location}, {value}% of adolescent mothers received timely prenatal and postpartum care.", "measure_type": "Percent", "unit": "Percent", @@ -3921,10 +4332,10 @@ "medicaid_first_prenatal_visit": { "id": "bundle_maternal_health/dist/maternal_state.parquet|measure=medicaid_first_prenatal_visit", "short_name": "First Prenatal Visit (Adolescent)", - "long_name": "First Prenatal Care Visit – Adolescents (Medicaid)", + "long_name": "First Prenatal Care Visit Adolescents (Medicaid)", "category": "maternal", "short_description": "Percent of adolescent females (Medicaid) with a first-trimester prenatal visit.", - "long_description": "Child Core Set measure (FPC). Percentage of adolescent females aged 15–20 enrolled in Medicaid who had a live birth and received a prenatal care visit in the first trimester. State-level, Medicaid payer.", + "long_description": "Child Core Set measure (FPC). Percentage of adolescent females aged 1520 enrolled in Medicaid who had a live birth and received a prenatal care visit in the first trimester. State-level, Medicaid payer.", "statement": "In {location}, {value}% of adolescent mothers received first-trimester prenatal care.", "measure_type": "Percent", "unit": "Percent", @@ -3937,11 +4348,11 @@ }, "medicaid_contraceptive_postpartum_adult": { "id": "bundle_maternal_health/dist/maternal_state.parquet|measure=medicaid_contraceptive_postpartum_adult", - "short_name": "Contraceptive Care – Postpartum (Adult)", - "long_name": "Contraceptive Care – Postpartum, Adults (Medicaid)", + "short_name": "Contraceptive Care Postpartum (Adult)", + "long_name": "Contraceptive Care Postpartum, Adults (Medicaid)", "category": "maternal", "short_description": "Percent of adult women (Medicaid) with a live birth who received postpartum contraceptive care.", - "long_description": "Adult Core Set measure (CPA). Percentage of women aged 21–44 enrolled in Medicaid who had a live birth and received a most or moderately effective contraceptive method within 60 days of delivery. State-level, Medicaid payer.", + "long_description": "Adult Core Set measure (CPA). Percentage of women aged 2144 enrolled in Medicaid who had a live birth and received a most or moderately effective contraceptive method within 60 days of delivery. State-level, Medicaid payer.", "statement": "In {location}, {value}% of adult women received postpartum contraceptive care.", "measure_type": "Percent", "unit": "Percent", @@ -3954,11 +4365,11 @@ }, "medicaid_contraceptive_postpartum_child": { "id": "bundle_maternal_health/dist/maternal_state.parquet|measure=medicaid_contraceptive_postpartum_child", - "short_name": "Contraceptive Care – Postpartum (Adolescent)", - "long_name": "Contraceptive Care – Postpartum, Adolescents (Medicaid)", + "short_name": "Contraceptive Care Postpartum (Adolescent)", + "long_name": "Contraceptive Care Postpartum, Adolescents (Medicaid)", "category": "maternal", "short_description": "Percent of adolescent females (Medicaid) with a live birth who received postpartum contraceptive care.", - "long_description": "Child Core Set measure (CPC). Percentage of adolescent females aged 15–20 enrolled in Medicaid who had a live birth and received a most or moderately effective contraceptive method within 60 days of delivery. State-level, Medicaid payer.", + "long_description": "Child Core Set measure (CPC). Percentage of adolescent females aged 1520 enrolled in Medicaid who had a live birth and received a most or moderately effective contraceptive method within 60 days of delivery. State-level, Medicaid payer.", "statement": "In {location}, {value}% of adolescent females received postpartum contraceptive care.", "measure_type": "Percent", "unit": "Percent", @@ -3989,7 +4400,7 @@ "medicaid_low_birthweight_risk_adjusted": { "id": "bundle_maternal_health/dist/maternal_state.parquet|measure=medicaid_low_birthweight_risk_adjusted", "short_name": "Low Birthweight, Risk-Adjusted (Medicaid)", - "long_name": "Live Births Weighing Less Than 2,500 Grams – Risk-Adjusted (Medicaid)", + "long_name": "Live Births Weighing Less Than 2,500 Grams Risk-Adjusted (Medicaid)", "category": "maternal", "short_description": "Risk-adjusted percent of live births (Medicaid) weighing less than 2,500 grams.", "long_description": "Child Core Set measure (LRCD). Risk-adjusted version of the low birthweight measure: percentage of live singleton deliveries resulting in low birthweight, adjusted for clinical and demographic risk factors. State-level, Medicaid payer.", @@ -4191,7 +4602,7 @@ "long_name": "Kindergarten non-medical MMR Vaccine Exemption Rate (County)", "category": "immunization", "short_description": "Percentage of kindergartners with non-medical exemptions from MMR vaccination requirements at county level.", - "long_description": "County-level percentage of kindergartners with non-medical exemptions from MMR vaccination requirements. Compiled from state-reported exemption data spanning 2009–2024. County-level coverage varies by state, as not all states report at the county level. Data from Fattah et al. 2026 (JAMA).", + "long_description": "County-level percentage of kindergartners with non-medical exemptions from MMR vaccination requirements. Compiled from state-reported exemption data spanning 20092024. County-level coverage varies by state, as not all states report at the county level. Data from Fattah et al. 2026 (JAMA).", "measure_type": "Percent", "unit": "%", "time_resolution": "Year", @@ -4275,7 +4686,7 @@ "long_name": "Kindergarten MMR Vaccine Exemption Rate (State)", "category": "immunization", "short_description": "Percentage of kindergartners with non-medical exemptions from MMR vaccination requirements at state level.", - "long_description": "State-level percentage of kindergartners with non-medical exemptions from MMR vaccination requirements. Compiled from state-reported exemption data spanning 2009–2024, covering prepandemic (2009–2019) and postpandemic (2020–2024) periods. Data from Fattah et al. 2026 (JAMA).", + "long_description": "State-level percentage of kindergartners with non-medical exemptions from MMR vaccination requirements. Compiled from state-reported exemption data spanning 20092024, covering prepandemic (20092019) and postpandemic (20202024) periods. Data from Fattah et al. 2026 (JAMA).", "measure_type": "Percent", "unit": "%", "time_resolution": "Year", @@ -4816,16 +5227,16 @@ }, { "name": "value_scale", - "short_name": "Scaled value (0–100)", - "description": "Primary value rescaled to 0–100 relative to the geography-level minimum and maximum.", + "short_name": "Scaled value (0100)", + "description": "Primary value rescaled to 0100 relative to the geography-level minimum and maximum.", "measure_type": "", "unit": "", "levels": {} }, { "name": "value_smooth_scale", - "short_name": "Smoothed scaled value (0–100)", - "description": "3-week smoothed value rescaled to 0–100 relative to the geography-level minimum and maximum.", + "short_name": "Smoothed scaled value (0100)", + "description": "3-week smoothed value rescaled to 0100 relative to the geography-level minimum and maximum.", "measure_type": "", "unit": "", "levels": {} @@ -4932,16 +5343,16 @@ }, { "name": "value_scale", - "short_name": "Scaled value (0–100)", - "description": "Primary value rescaled to 0–100 relative to the geography-level minimum and maximum.", + "short_name": "Scaled value (0100)", + "description": "Primary value rescaled to 0100 relative to the geography-level minimum and maximum.", "measure_type": "", "unit": "", "levels": {} }, { "name": "value_smooth_scale", - "short_name": "Smoothed scaled value (0–100)", - "description": "3-week smoothed value rescaled to 0–100 relative to the geography-level minimum and maximum.", + "short_name": "Smoothed scaled value (0100)", + "description": "3-week smoothed value rescaled to 0100 relative to the geography-level minimum and maximum.", "measure_type": "", "unit": "", "levels": {} @@ -5046,16 +5457,16 @@ }, { "name": "value_scale", - "short_name": "Scaled value (0–100)", - "description": "Primary value rescaled to 0–100 relative to the geography-level minimum and maximum.", + "short_name": "Scaled value (0100)", + "description": "Primary value rescaled to 0100 relative to the geography-level minimum and maximum.", "measure_type": "", "unit": "", "levels": {} }, { "name": "value_smooth_scale", - "short_name": "Smoothed scaled value (0–100)", - "description": "3-week smoothed value rescaled to 0–100 relative to the geography-level minimum and maximum.", + "short_name": "Smoothed scaled value (0100)", + "description": "3-week smoothed value rescaled to 0100 relative to the geography-level minimum and maximum.", "measure_type": "", "unit": "", "levels": {} @@ -5165,16 +5576,16 @@ }, { "name": "value_scale", - "short_name": "Scaled value (0–100)", - "description": "Primary value rescaled to 0–100 relative to the geography-level minimum and maximum.", + "short_name": "Scaled value (0100)", + "description": "Primary value rescaled to 0100 relative to the geography-level minimum and maximum.", "measure_type": "", "unit": "", "levels": {} }, { "name": "value_smooth_scale", - "short_name": "Smoothed scaled value (0–100)", - "description": "3-week smoothed value rescaled to 0–100 relative to the geography-level minimum and maximum.", + "short_name": "Smoothed scaled value (0100)", + "description": "3-week smoothed value rescaled to 0100 relative to the geography-level minimum and maximum.", "measure_type": "", "unit": "", "levels": {} @@ -5237,9 +5648,9 @@ ] }, { - "filename": "pneumococcus_by_geography_year.parquet", - "path": "data/bundle_respiratory/dist/pneumococcus_by_geography_year.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_respiratory/dist/pneumococcus_by_geography_year.parquet", + "filename": "pneumococcus_by_geography.parquet", + "path": "data/bundle_respiratory/dist/pneumococcus_by_geography.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_respiratory/dist/pneumococcus_by_geography.parquet", "columns": [ { "name": "serotype", @@ -5280,21 +5691,13 @@ "measure_type": "", "unit": "", "levels": {} - }, - { - "name": "value_smooth", - "short_name": "Pneumococcal IPD % (3-year smoothed)", - "description": "3-year rolling average of the percent of IPD cases caused by each pneumococcal serotype.", - "measure_type": "Percent", - "unit": "%", - "levels": {} } ] }, { - "filename": "pneumococcus_by_geography.parquet", - "path": "data/bundle_respiratory/dist/pneumococcus_by_geography.parquet", - "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_respiratory/dist/pneumococcus_by_geography.parquet", + "filename": "pneumococcus_by_geography_year.parquet", + "path": "data/bundle_respiratory/dist/pneumococcus_by_geography_year.parquet", + "url": "https://raw.githubusercontent.com/PopHIVE/Ingest/main/data/bundle_respiratory/dist/pneumococcus_by_geography_year.parquet", "columns": [ { "name": "serotype", @@ -5335,6 +5738,14 @@ "measure_type": "", "unit": "", "levels": {} + }, + { + "name": "value_smooth", + "short_name": "Pneumococcal IPD % (3-year smoothed)", + "description": "3-year rolling average of the percent of IPD cases caused by each pneumococcal serotype.", + "measure_type": "Percent", + "unit": "%", + "levels": {} } ] }, @@ -5553,16 +5964,16 @@ }, { "name": "value_scale", - "short_name": "Scaled value (0–100)", - "description": "Primary value rescaled to 0–100 relative to the geography-level minimum and maximum.", + "short_name": "Scaled value (0100)", + "description": "Primary value rescaled to 0100 relative to the geography-level minimum and maximum.", "measure_type": "", "unit": "", "levels": {} }, { "name": "value_smooth_scale", - "short_name": "Smoothed scaled value (0–100)", - "description": "3-week smoothed value rescaled to 0–100 relative to the geography-level minimum and maximum.", + "short_name": "Smoothed scaled value (0100)", + "description": "3-week smoothed value rescaled to 0100 relative to the geography-level minimum and maximum.", "measure_type": "", "unit": "", "levels": {} @@ -5820,16 +6231,16 @@ }, { "name": "value_scale", - "short_name": "Scaled value (0–100)", - "description": "Primary value rescaled to 0–100 relative to the geography-level minimum and maximum.", + "short_name": "Scaled value (0100)", + "description": "Primary value rescaled to 0100 relative to the geography-level minimum and maximum.", "measure_type": "", "unit": "", "levels": {} }, { "name": "value_smooth_scale", - "short_name": "Smoothed scaled value (0–100)", - "description": "3-week smoothed value rescaled to 0–100 relative to the geography-level minimum and maximum.", + "short_name": "Smoothed scaled value (0100)", + "description": "3-week smoothed value rescaled to 0100 relative to the geography-level minimum and maximum.", "measure_type": "", "unit": "", "levels": {} @@ -9014,58 +9425,440 @@ } }, { - "name": "value", - "short_name": "Value", - "description": "Primary measure value. Units vary by measure -- see the measure's own unit. Rows flagged suppressed or not_asked do NOT carry a usable value; see those columns.", + "name": "value", + "short_name": "Value", + "description": "Primary measure value. Units vary by measure -- see the measure's own unit. Rows flagged suppressed or not_asked do NOT carry a usable value; see those columns.", + "measure_type": "", + "unit": "", + "levels": {} + }, + { + "name": "lcl", + "short_name": "Lower confidence limit", + "description": "Lower bound of the 95% confidence interval on value, where the source supplies one.", + "measure_type": "", + "unit": "", + "levels": {} + }, + { + "name": "ucl", + "short_name": "Upper confidence limit", + "description": "Upper bound of the 95% confidence interval on value, where the source supplies one.", + "measure_type": "", + "unit": "", + "levels": {} + }, + { + "name": "suppressed", + "short_name": "Suppressed flag", + "description": "1 if the source suppressed the estimate. Suppressed YRBSS rows carry value = 0; suppressed Epic Cosmos rows carry an imputed count of 5, which makes the derived rate meaningless and can push it into the tens of thousands per 100,000. Filter on suppressed == 0 before using value.", + "measure_type": "", + "unit": "", + "levels": {} + }, + { + "name": "not_asked", + "short_name": "Not asked flag", + "description": "YRBSS only. 1 if the question was not asked in that jurisdiction and year. These rows carry value = 0, which is not an estimate -- filter on not_asked == 0 before using value.", + "measure_type": "", + "unit": "", + "levels": {} + } + ] + } + ] + } + }, + "data_sources": { + "NREVSS": { + "name": "NREVSS", + "display_name": "NREVSS", + "description": "The National Respiratory and Enteric Virus Surveillance System (NREVSS) is a voluntary, laboratory-based surveillance system that monitors temporal and geographic trends for respiratory syncytial virus (RSV), human parainfluenza viruses, respiratory adenoviruses, human metapneumovirus, human coronaviruses, and rotavirus circulation in the United States. Participating laboratories report weekly to CDC on the number of tests performed and the number positive for each virus. NREVSS data are used to characterize seasonal patterns of these viruses and to help public health officials anticipate and prepare for outbreaks. Data are aggregated at the HHS regional and national levels. The system has been operational since 1987 and includes approximately 300 participating laboratories across the United States.", + "standard_files": [ + { + "filename": "data.csv.gz", + "columns": [ + { + "name": "source", + "short_name": "Source", + "description": "Data source", + "measure_type": "", + "unit": "categorical" + }, + { + "name": "geography", + "short_name": "Geography", + "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", + "measure_type": "identifier", + "unit": "FIPS code" + }, + { + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date" + }, + { + "name": "scaled_cases", + "short_name": "Scale Cases", + "description": "Number of positive tests per week divided by the highest number of positive tests for that region", + "measure_type": "scaled positive tests", + "unit": "scaled number" + }, + { + "name": "pcr_detections", + "short_name": "PCR detections", + "description": "Number of positive tests per week by HHS region", + "measure_type": "Number of positive tests", + "unit": "Number" + }, + { + "name": "epiyr", + "short_name": "Epi_year", + "description": "Epidemiological year", + "measure_type": "year", + "unit": "year" + }, + { + "name": "epiwk", + "short_name": "Epi_week", + "description": "Epidemiological week", + "measure_type": "year", + "unit": "year" + }, + { + "name": "week", + "short_name": "week", + "description": "Calendar week", + "measure_type": "week", + "unit": "week" + }, + { + "name": "year", + "short_name": "year", + "description": "Calendar year", + "measure_type": "year", + "unit": "year" + } + ] + } + ] + }, + "abcs": { + "name": "abcs", + "display_name": "Abcs", + "description": "CDC monitors invasive bacterial infections that cause bloodstream infections, sepsis, and meningitis in persons living in the community through Active Bacterial Core surveillance (ABCs). ABCs conducts laboratory- and population-based surveillance for invasive pneumococcal disease (IPD). ABCs serotype data are used to measure the impact of vaccine use in the United States on vaccine-type IPD. This table reports IPD case counts in the ABCs catchment area by serotype for years 1998 through 2022. Cases are grouped into the following mutually exclusive age groups: age <2 years old, age 2-4 years old, age 5-17 years old, age 18-49 years old, age 50-64 years old, and age >=65 years old. ABCs methods and surveillance areas reporting IPD cases has changed over time. Given these changes, trends in serotype distribution by year and age group should be interpreted with caution. The all-site summary presented here is calculated based on the 8 sites that consistently report to ABCs and differs from the All-site measure provided by the source. Additional information on ABCs methods and surveillance population is available at https://www.cdc.gov/abcs/methodology/index.html. Analyze and visualize data using the ABCs Bact Facts Interactive Data Dashboard at https://www.cdc.gov/abcs/bact-facts-interactive-dashboard. ABCs IPD Isolates were serotyped by Quellung, PCR, or whole genome sequencing (WGS). Cases without an isolate available or with mixed serotypes reported are listed on the table as MISS. Additionally, non-typeable IPD cases are shown as NT. Zero cell rows were not included in this dataset. Minor changes to previous years serotype data can occur as additional isolates and serotype data become available. Cases were excluded from this dataset if the ABCs site did not perform surveillance in the catchment area for a full calendar year. As a result, cases were excluded from the following sites: TN, 11 counties, Jul-Dec 1999; CO, 5 counties, Jul-Dec 2000; CA, 2 counties (aged <5 years), Oct-Dec 2000.", + "standard_files": [ + { + "filename": "data.csv.gz", + "columns": [ + { + "name": "geography", + "short_name": "Geography", + "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", + "measure_type": "identifier", + "unit": "FIPS code" + }, + { + "name": "age", + "short_name": "Age group", + "description": "", + "measure_type": "Age group (years)", + "unit": "years" + }, + { + "name": "serotype", + "short_name": "Serotype", + "description": "Pneumococcal serotype", + "measure_type": "Category", + "unit": "" + }, + { + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date" + }, + { + "name": "N_IPD", + "short_name": "Number of IPD episodes", + "description": "Pneumococcal serotype", + "measure_type": "count", + "unit": "Number" + }, + { + "name": "pct_IPD", + "short_name": "Percent of IPD episodes", + "description": "Pneumococcal serotype", + "measure_type": "percent", + "unit": "%" + }, + { + "name": "pop", + "short_name": "pop", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "rate_IPD", + "short_name": "IPD incidence rate", + "description": "Annual rate of invasive pneumococcal disease cases per 100,000 persons in the ABCs catchment area", + "measure_type": "Rate", + "unit": "Cases per 100,000" + } + ] + }, + { + "filename": "uad.csv.gz", + "columns": [ + { + "name": "geography", + "short_name": "Geography", + "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", + "measure_type": "identifier", + "unit": "FIPS code" + }, + { + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date" + }, + { + "name": "serotype", + "short_name": "Serotype", + "description": "Pneumococcal serotype", + "measure_type": "Category", + "unit": "" + }, + { + "name": "N_SSUAD", + "short_name": "Number of non-invasive pneumococcal pneumonia episodes", + "description": "Pneumococcal serotype", + "measure_type": "count", + "unit": "Number" + } + ] + } + ] + }, + "abcs_gas": { + "name": "abcs_gas", + "display_name": "Abcs Gas", + "description": "CDC monitors invasive bacterial infections through Active Bacterial Core surveillance (ABCs), a population-based surveillance program for invasive bacterial diseases in selected geographic areas of the United States. This dataset reports annual data on invasive Group A Streptococcus (iGAS) disease from 1997 onwards, including case and death rates by age group, sex, and race; clinical syndrome distribution (cellulitis, bacteremia without focus, pneumonia, necrotizing fasciitis, streptococcal toxic shock syndrome); antibiotic resistance patterns; and emm type distribution among isolates. ABCs catchment areas include California, Colorado, Connecticut, Georgia, Maryland, Minnesota, New York, Oregon, and Tennessee, representing approximately 10% of the US population. Incidence rates are calculated using U.S. Census Bureau population estimates for the respective catchment areas.", + "standard_files": [ + { + "filename": "data.csv.gz", + "columns": [ + { + "name": "geography", + "short_name": "Geography", + "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", + "measure_type": "identifier", + "unit": "FIPS code" + }, + { + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date" + }, + { + "name": "age", + "short_name": "Age Group", + "description": "Age group category", + "measure_type": "category", + "unit": "" + }, + { + "name": "sex", + "short_name": "Sex", + "description": "Sex category (Male, Female, Overall)", + "measure_type": "category", + "unit": "" + }, + { + "name": "race_ethnicity", + "short_name": "Race/Ethnicity", + "description": "Race/ethnicity category", + "measure_type": "category", + "unit": "" + }, + { + "name": "abcs_gas_rate_cases", + "short_name": "abcs_gas_rate_cases", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_rate_deaths", + "short_name": "abcs_gas_rate_deaths", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_N_cases", + "short_name": "abcs_gas_N_cases", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_N_deaths", + "short_name": "abcs_gas_N_deaths", + "description": "", + "measure_type": "", + "unit": "" + } + ] + }, + { + "filename": "data_emm.csv.gz", + "columns": [ + { + "name": "geography", + "short_name": "Geography", + "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", + "measure_type": "identifier", + "unit": "FIPS code" + }, + { + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date" + }, + { + "name": "abcs_gas_emm_count_number_of_isolates", + "short_name": "abcs_gas_emm_count_number_of_isolates", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_emm_pct_other", + "short_name": "abcs_gas_emm_pct_other", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_emm_pct_emm_1", + "short_name": "abcs_gas_emm_pct_emm_1", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_emm_pct_emm_11", + "short_name": "abcs_gas_emm_pct_emm_11", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_emm_pct_emm_12", + "short_name": "abcs_gas_emm_pct_emm_12", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_emm_pct_emm_28", + "short_name": "abcs_gas_emm_pct_emm_28", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_emm_pct_emm_43", + "short_name": "abcs_gas_emm_pct_emm_43", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_emm_pct_emm_59", + "short_name": "abcs_gas_emm_pct_emm_59", + "description": "", "measure_type": "", - "unit": "", - "levels": {} + "unit": "" }, { - "name": "lcl", - "short_name": "Lower confidence limit", - "description": "Lower bound of the 95% confidence interval on value, where the source supplies one.", + "name": "abcs_gas_emm_pct_emm_77", + "short_name": "abcs_gas_emm_pct_emm_77", + "description": "", "measure_type": "", - "unit": "", - "levels": {} + "unit": "" }, { - "name": "ucl", - "short_name": "Upper confidence limit", - "description": "Upper bound of the 95% confidence interval on value, where the source supplies one.", + "name": "abcs_gas_emm_pct_emm_82", + "short_name": "abcs_gas_emm_pct_emm_82", + "description": "", "measure_type": "", - "unit": "", - "levels": {} + "unit": "" }, { - "name": "suppressed", - "short_name": "Suppressed flag", - "description": "1 if the source suppressed the estimate. Suppressed YRBSS rows carry value = 0; suppressed Epic Cosmos rows carry an imputed count of 5, which makes the derived rate meaningless and can push it into the tens of thousands per 100,000. Filter on suppressed == 0 before using value.", + "name": "abcs_gas_emm_pct_emm_83", + "short_name": "abcs_gas_emm_pct_emm_83", + "description": "", "measure_type": "", - "unit": "", - "levels": {} + "unit": "" }, { - "name": "not_asked", - "short_name": "Not asked flag", - "description": "YRBSS only. 1 if the question was not asked in that jurisdiction and year. These rows carry value = 0, which is not an estimate -- filter on not_asked == 0 before using value.", + "name": "abcs_gas_emm_pct_emm_89", + "short_name": "abcs_gas_emm_pct_emm_89", + "description": "", "measure_type": "", - "unit": "", - "levels": {} + "unit": "" + }, + { + "name": "abcs_gas_emm_pct_emm_92", + "short_name": "abcs_gas_emm_pct_emm_92", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_emm_pct_emm_49", + "short_name": "abcs_gas_emm_pct_emm_49", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_emm_pct_emm_81", + "short_name": "abcs_gas_emm_pct_emm_81", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_emm_pct_emm_60", + "short_name": "abcs_gas_emm_pct_emm_60", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_emm_pct_emm_91", + "short_name": "abcs_gas_emm_pct_emm_91", + "description": "", + "measure_type": "", + "unit": "" } ] - } - ] - } - }, - "data_sources": { - "abcs": { - "name": "abcs", - "display_name": "Abcs", - "description": "CDC monitors invasive bacterial infections that cause bloodstream infections, sepsis, and meningitis in persons living in the community through Active Bacterial Core surveillance (ABCs). ABCs conducts laboratory- and population-based surveillance for invasive pneumococcal disease (IPD). ABCs serotype data are used to measure the impact of vaccine use in the United States on vaccine-type IPD. This table reports IPD case counts in the ABCs catchment area by serotype for years 1998 through 2022. Cases are grouped into the following mutually exclusive age groups: age <2 years old, age 2-4 years old, age 5-17 years old, age 18-49 years old, age 50-64 years old, and age >=65 years old. ABCs methods and surveillance areas reporting IPD cases has changed over time. Given these changes, trends in serotype distribution by year and age group should be interpreted with caution. The all-site summary presented here is calculated based on the 8 sites that consistently report to ABCs and differs from the All-site measure provided by the source. Additional information on ABCs methods and surveillance population is available at https://www.cdc.gov/abcs/methodology/index.html. Analyze and visualize data using the ABCs Bact Facts Interactive Data Dashboard at https://www.cdc.gov/abcs/bact-facts-interactive-dashboard. ABCs IPD Isolates were serotyped by Quellung, PCR, or whole genome sequencing (WGS). Cases without an isolate available or with mixed serotypes reported are listed on the table as MISS. Additionally, non-typeable IPD cases are shown as NT. Zero cell rows were not included in this dataset. Minor changes to previous years serotype data can occur as additional isolates and serotype data become available. Cases were excluded from this dataset if the ABCs site did not perform surveillance in the catchment area for a full calendar year. As a result, cases were excluded from the following sites: TN, 11 counties, Jul-Dec 1999; CO, 5 counties, Jul-Dec 2000; CA, 2 counties (aged <5 years), Oct-Dec 2000.", - "standard_files": [ + }, { - "filename": "data.csv.gz", + "filename": "data_resistance.csv.gz", "columns": [ { "name": "geography", @@ -9075,58 +9868,65 @@ "unit": "FIPS code" }, { - "name": "age", - "short_name": "Age group", + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date" + }, + { + "name": "abcs_gas_pct_resistant_cefotaxime", + "short_name": "abcs_gas_pct_resistant_cefotaxime", "description": "", - "measure_type": "Age group (years)", - "unit": "years" + "measure_type": "", + "unit": "" }, { - "name": "serotype", - "short_name": "Serotype", - "description": "Pneumococcal serotype", - "measure_type": "Category", + "name": "abcs_gas_pct_resistant_clindamycin", + "short_name": "abcs_gas_pct_resistant_clindamycin", + "description": "", + "measure_type": "", "unit": "" }, { - "name": "time", - "short_name": "Time", - "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", - "measure_type": "date", - "unit": "date" + "name": "abcs_gas_pct_resistant_erythromycin", + "short_name": "abcs_gas_pct_resistant_erythromycin", + "description": "", + "measure_type": "", + "unit": "" }, { - "name": "N_IPD", - "short_name": "Number of IPD episodes", - "description": "Pneumococcal serotype", - "measure_type": "count", - "unit": "Number" + "name": "abcs_gas_pct_resistant_penicillin", + "short_name": "abcs_gas_pct_resistant_penicillin", + "description": "", + "measure_type": "", + "unit": "" }, { - "name": "pct_IPD", - "short_name": "Percent of IPD episodes", - "description": "Pneumococcal serotype", - "measure_type": "percent", - "unit": "%" + "name": "abcs_gas_pct_resistant_tetracycline", + "short_name": "abcs_gas_pct_resistant_tetracycline", + "description": "", + "measure_type": "", + "unit": "" }, { - "name": "pop", - "short_name": "pop", + "name": "abcs_gas_pct_resistant_vancomycin", + "short_name": "abcs_gas_pct_resistant_vancomycin", "description": "", "measure_type": "", "unit": "" }, { - "name": "rate_IPD", - "short_name": "IPD incidence rate", - "description": "Annual rate of invasive pneumococcal disease cases per 100,000 persons in the ABCs catchment area", - "measure_type": "Rate", - "unit": "Cases per 100,000" + "name": "abcs_gas_n_isolates", + "short_name": "abcs_gas_n_isolates", + "description": "", + "measure_type": "", + "unit": "" } ] }, { - "filename": "uad.csv.gz", + "filename": "data_syndromes.csv.gz", "columns": [ { "name": "geography", @@ -9143,18 +9943,39 @@ "unit": "date" }, { - "name": "serotype", - "short_name": "Serotype", - "description": "Pneumococcal serotype", - "measure_type": "Category", + "name": "abcs_gas_pct_syndrome_cellulitis", + "short_name": "abcs_gas_pct_syndrome_cellulitis", + "description": "", + "measure_type": "", "unit": "" }, { - "name": "N_SSUAD", - "short_name": "Number of non-invasive pneumococcal pneumonia episodes", - "description": "Pneumococcal serotype", - "measure_type": "count", - "unit": "Number" + "name": "abcs_gas_pct_syndrome_bacteremia_without_focus", + "short_name": "abcs_gas_pct_syndrome_bacteremia_without_focus", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_pct_syndrome_pneumonia", + "short_name": "abcs_gas_pct_syndrome_pneumonia", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_pct_syndrome_necrotizing_fasciitis", + "short_name": "abcs_gas_pct_syndrome_necrotizing_fasciitis", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "abcs_gas_pct_syndrome_strep_toxic_shock", + "short_name": "abcs_gas_pct_syndrome_strep_toxic_shock", + "description": "", + "measure_type": "", + "unit": "" } ] } @@ -9206,9 +10027,9 @@ { "name": "ahrf_rural_urban_code", "short_name": "Rural-Urban Code", - "description": "USDA rural-urban continuum code classifying counties from metro to rural (1–9).", + "description": "USDA rural-urban continuum code classifying counties from metro to rural (19).", "measure_type": "Category", - "unit": "Code 1–9 (1=large metro, 9=most rural)" + "unit": "Code 19 (1=large metro, 9=most rural)" }, { "name": "ahrf_md_all", @@ -9276,9 +10097,9 @@ { "name": "ahrf_pm25", "short_name": "PM2.5 Annual Avg", - "description": "Annual average PM2.5 concentration (μg/m³) from EPA monitoring data.", + "description": "Annual average PM2.5 concentration (g/m) from EPA monitoring data.", "measure_type": "Rate", - "unit": "μg/m³" + "unit": "g/m" }, { "name": "ahrf_medicare_per_capita", @@ -9421,108 +10242,19 @@ { "name": "beam_outbreak_isolates_vibrio", "short_name": "Vibrio", - "description": "Monthly count of Vibrio isolates linked to a recognized outbreak.", - "measure_type": "Count", - "unit": "Number of isolates" - } - ] - } - ] - }, - "brfss": { - "name": "brfss", - "display_name": "BRFSS", - "description": "The Behavioral Risk Factor Surveillance System (BRFSS) is the nation's premier system of health-related telephone surveys that collect state data about U.S. residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. Established in 1984 with 15 states, BRFSS now collects data in all 50 states, the District of Columbia, and three U.S. territories, completing more than 400,000 adult interviews each year. BRFSS provides state-specific data on health conditions including obesity, diabetes, depression, and health behaviors such as heavy drinking, physical activity, and tobacco use. Data are available by age, sex, race/ethnicity, and education level. BRFSS is a critical resource for public health surveillance and policy-making at both state and national levels.", - "standard_files": [ - { - "filename": "data_survey.csv.gz", - "columns": [ - { - "name": "geography", - "short_name": "Geography", - "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", - "measure_type": "identifier", - "unit": "FIPS code" - }, - { - "name": "time", - "short_name": "Time", - "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", - "measure_type": "date", - "unit": "date" - }, - { - "name": "age", - "short_name": "Age", - "description": "Age group.", - "measure_type": "integer", - "unit": "years" - }, - { - "name": "prev_diabetes_survey", - "short_name": "Diabetes Prevalence (Survey)", - "description": "Estimated diabetes prevalence from BRFSS survey data.", - "measure_type": "percent", - "unit": "percent" - }, - { - "name": "prev_diabetes_survey_lcl", - "short_name": "Diabetes Prevalence Lower CI", - "description": "Lower bound of 95% confidence interval for diabetes prevalence.", - "measure_type": "percent", - "unit": "percent" - }, - { - "name": "prev_diabetes_survey_ucl", - "short_name": "Diabetes Prevalence Upper CI", - "description": "Upper bound of 95% confidence interval for diabetes prevalence.", - "measure_type": "percent", - "unit": "percent" - }, - { - "name": "prev_obesity_survey", - "short_name": "Obesity Prevalence (Survey)", - "description": "Estimated obesity prevalence (BMI >= 30) from BRFSS survey data.", - "measure_type": "percent", - "unit": "percent" - }, - { - "name": "prev_obesity_survey_lcl", - "short_name": "Obesity Prevalence Lower CI", - "description": "Lower bound of 95% confidence interval for obesity prevalence.", - "measure_type": "percent", - "unit": "percent" - }, - { - "name": "prev_obesity_survey_ucl", - "short_name": "Obesity Prevalence Upper CI", - "description": "Upper bound of 95% confidence interval for obesity prevalence.", - "measure_type": "percent", - "unit": "percent" - }, - { - "name": "agec", - "short_name": "Age Category", - "description": "Categorical age grouping used in survey analysis.", - "measure_type": "categorical", - "unit": "category" - }, - { - "name": "sample_size_diab", - "short_name": "Sample Size (Diabetes)", - "description": "Number of survey respondents used to estimate diabetes prevalence.", - "measure_type": "integer", - "unit": "count" - }, - { - "name": "sample_size_obesity", - "short_name": "Sample Size (Obesity)", - "description": "Number of survey respondents used to estimate obesity prevalence.", - "measure_type": "integer", - "unit": "count" + "description": "Monthly count of Vibrio isolates linked to a recognized outbreak.", + "measure_type": "Count", + "unit": "Number of isolates" } ] - }, + } + ] + }, + "brfss": { + "name": "brfss", + "display_name": "BRFSS", + "description": "The Behavioral Risk Factor Surveillance System (BRFSS) is the nation's premier system of health-related telephone surveys that collect state data about U.S. residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. Established in 1984 with 15 states, BRFSS now collects data in all 50 states, the District of Columbia, and three U.S. territories, completing more than 400,000 adult interviews each year. BRFSS provides state-specific data on health conditions including obesity, diabetes, depression, and health behaviors such as heavy drinking, physical activity, and tobacco use. Data are available by age, sex, race/ethnicity, and education level. BRFSS is a critical resource for public health surveillance and policy-making at both state and national levels.", + "standard_files": [ { "filename": "data.csv.gz", "columns": [ @@ -9660,6 +10392,95 @@ "unit": "percent" } ] + }, + { + "filename": "data_survey.csv.gz", + "columns": [ + { + "name": "geography", + "short_name": "Geography", + "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", + "measure_type": "identifier", + "unit": "FIPS code" + }, + { + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date" + }, + { + "name": "age", + "short_name": "Age", + "description": "Age group.", + "measure_type": "integer", + "unit": "years" + }, + { + "name": "prev_diabetes_survey", + "short_name": "Diabetes Prevalence (Survey)", + "description": "Estimated diabetes prevalence from BRFSS survey data.", + "measure_type": "percent", + "unit": "percent" + }, + { + "name": "prev_diabetes_survey_lcl", + "short_name": "Diabetes Prevalence Lower CI", + "description": "Lower bound of 95% confidence interval for diabetes prevalence.", + "measure_type": "percent", + "unit": "percent" + }, + { + "name": "prev_diabetes_survey_ucl", + "short_name": "Diabetes Prevalence Upper CI", + "description": "Upper bound of 95% confidence interval for diabetes prevalence.", + "measure_type": "percent", + "unit": "percent" + }, + { + "name": "prev_obesity_survey", + "short_name": "Obesity Prevalence (Survey)", + "description": "Estimated obesity prevalence (BMI >= 30) from BRFSS survey data.", + "measure_type": "percent", + "unit": "percent" + }, + { + "name": "prev_obesity_survey_lcl", + "short_name": "Obesity Prevalence Lower CI", + "description": "Lower bound of 95% confidence interval for obesity prevalence.", + "measure_type": "percent", + "unit": "percent" + }, + { + "name": "prev_obesity_survey_ucl", + "short_name": "Obesity Prevalence Upper CI", + "description": "Upper bound of 95% confidence interval for obesity prevalence.", + "measure_type": "percent", + "unit": "percent" + }, + { + "name": "agec", + "short_name": "Age Category", + "description": "Categorical age grouping used in survey analysis.", + "measure_type": "categorical", + "unit": "category" + }, + { + "name": "sample_size_diab", + "short_name": "Sample Size (Diabetes)", + "description": "Number of survey respondents used to estimate diabetes prevalence.", + "measure_type": "integer", + "unit": "count" + }, + { + "name": "sample_size_obesity", + "short_name": "Sample Size (Obesity)", + "description": "Number of survey respondents used to estimate obesity prevalence.", + "measure_type": "integer", + "unit": "count" + } + ] } ] }, @@ -9851,7 +10672,7 @@ "census": { "name": "census", "display_name": "Census", - "description": "The 2020 Census Urban Area to County Allocation File maps Census-defined urban areas (urbanized areas with population ≥ 50,000 and urban clusters with population 2,500–49,999) to counties. Each row represents a county-urban area intersection and includes the share of county population, land area, and housing units within that urban area. Summing across all urban areas for a county yields total percent urban. Counties not appearing in the file have no urban area and are considered 100% rural. Urban area boundaries are based on the 2020 decennial Census and reflect the updated delineation methodology that increased the minimum population threshold for urbanized areas from 50,000 to 50,000 and revised cluster definitions.", + "description": "The 2020 Census Urban Area to County Allocation File maps Census-defined urban areas (urbanized areas with population 50,000 and urban clusters with population 2,50049,999) to counties. Each row represents a county-urban area intersection and includes the share of county population, land area, and housing units within that urban area. Summing across all urban areas for a county yields total percent urban. Counties not appearing in the file have no urban area and are considered 100% rural. Urban area boundaries are based on the 2020 decennial Census and reflect the updated delineation methodology that increased the minimum population threshold for urbanized areas from 50,000 to 50,000 and revised cluster definitions.", "standard_files": [ { "filename": "data_county.csv.gz", @@ -9882,63 +10703,63 @@ "short_name": "Broadband internet subscription rate", "description": "Share of households with a broadband internet subscription.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_BTH", - "short_name": "Birth rate (women 15–50)", - "description": "Share of women aged 15–50 who gave birth in the past 12 months.", + "short_name": "Birth rate (women 1550)", + "description": "Share of women aged 1550 who gave birth in the past 12 months.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DCY", "short_name": "Opportunity youth rate", - "description": "Share of youth aged 16–24 who are neither enrolled in school nor employed.", + "description": "Share of youth aged 1624 who are neither enrolled in school nor employed.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_EDB", "short_name": "High school graduation rate", "description": "Share of adults aged 25+ who have at least a high school diploma or equivalent.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_EDC", "short_name": "Higher education attainment rate", "description": "Share of adults aged 25+ who have attended any college or higher.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_GNI", "short_name": "Gini income inequality index", "description": "Measure of household income inequality (0=perfect equality, 1=maximum inequality).", "measure_type": "Index", - "unit": "Index (0–1)" + "unit": "Index (01)" }, { "name": "acs_GRP", "short_name": "Group quarters rate", "description": "Share of the total population living in group quarters (prisons, dorms, nursing homes, etc.).", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HBS", "short_name": "Severe housing cost burden rate", "description": "Share of households spending 50% or more of income on housing costs.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HBU", "short_name": "Housing cost burden rate", "description": "Share of households spending 30% or more of income on housing costs.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_POP", @@ -9963,29 +10784,29 @@ }, { "name": "acs_POP_I", - "short_name": "Infant population (0–4 years)", - "description": "Total count of infants aged 0–4 years.", + "short_name": "Infant population (04 years)", + "description": "Total count of infants aged 04 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_J", - "short_name": "Juvenile population (5–17 years)", - "description": "Total count of children and adolescents aged 5–17 years.", + "short_name": "Juvenile population (517 years)", + "description": "Total count of children and adolescents aged 517 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_Y", - "short_name": "Young adult population (18–39 years)", - "description": "Total count of young adults aged 18–39 years.", + "short_name": "Young adult population (1839 years)", + "description": "Total count of young adults aged 1839 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_O", - "short_name": "Middle-aged adult population (40–64 years)", - "description": "Total count of middle-aged adults aged 40–64 years.", + "short_name": "Middle-aged adult population (4064 years)", + "description": "Total count of middle-aged adults aged 4064 years.", "measure_type": "Count", "unit": "Persons" }, @@ -10001,54 +10822,54 @@ "short_name": "Male share of population", "description": "Proportion of the population that is male.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_F", "short_name": "Female share of population", "description": "Proportion of the population that is female.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_I", - "short_name": "Infant share of population (0–4 years)", - "description": "Proportion of the population aged 0–4 years.", + "short_name": "Infant share of population (04 years)", + "description": "Proportion of the population aged 04 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_J", - "short_name": "Juvenile share of population (5–17 years)", - "description": "Proportion of the population aged 5–17 years.", + "short_name": "Juvenile share of population (517 years)", + "description": "Proportion of the population aged 517 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_Y", - "short_name": "Young adult share of population (18–39 years)", - "description": "Proportion of the population aged 18–39 years.", + "short_name": "Young adult share of population (1839 years)", + "description": "Proportion of the population aged 1839 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_O", - "short_name": "Middle-aged adult share of population (40–64 years)", - "description": "Proportion of the population aged 40–64 years.", + "short_name": "Middle-aged adult share of population (4064 years)", + "description": "Proportion of the population aged 4064 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_S", "short_name": "Senior share of population (65+ years)", "description": "Proportion of the population aged 65 years and older.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DEP", "short_name": "Age dependency ratio", - "description": "Ratio of dependents (ages 0–17 and 65+) to working-age adults (ages 18–64).", + "description": "Ratio of dependents (ages 017 and 65+) to working-age adults (ages 1864).", "measure_type": "Ratio", "unit": "Ratio" }, @@ -10106,140 +10927,140 @@ "short_name": "Non-Hispanic White share", "description": "Proportion of the population that is Non-Hispanic White.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_B", "short_name": "Non-Hispanic Black share", "description": "Proportion of the population that is Non-Hispanic Black or African American.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_P", "short_name": "Native American share", "description": "Proportion of the population that is Non-Hispanic American Indian and Alaska Native.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_A", "short_name": "Asian share", "description": "Proportion of the population that is Non-Hispanic Asian.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_P1", "short_name": "Pacific Islander/Native Hawaiian share", "description": "Proportion of the population that is Non-Hispanic Native Hawaiian and Other Pacific Islander.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_Q", "short_name": "Two or more races share", "description": "Proportion of the population identifying as Non-Hispanic two or more races.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_H", "short_name": "Hispanic or Latino share", "description": "Proportion of the population that is Hispanic or Latino.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_REX", "short_name": "Race-Ethnicity Diversity Index", "description": "Probability that two randomly chosen residents are from different racial/ethnic groups (0=no diversity, ~1=maximum diversity).", "measure_type": "Index", - "unit": "Index (0–1)" + "unit": "Index (01)" }, { "name": "acs_HTA", "short_name": "Single-parent household rate", "description": "Share of family households headed by a single parent with children.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HTJ", "short_name": "Crowded housing rate", "description": "Share of occupied housing units with more than 1 person per room.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUF", "short_name": "Incomplete plumbing rate", "description": "Share of housing units without complete indoor plumbing.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUG", "short_name": "No telephone service rate", "description": "Share of occupied housing units without telephone service.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUN", "short_name": "Mobile home rate", "description": "Share of housing units that are mobile homes or trailers.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUO", "short_name": "Owner-occupied housing rate", "description": "Share of occupied housing units that are owner-occupied.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_POV", "short_name": "Poverty rate", "description": "Share of the population with income below the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PUB", "short_name": "Public transit commute rate", "description": "Share of workers who commute primarily by public transportation.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVA", "short_name": "Deep poverty rate (<50% FPL)", "description": "Share of the population with income below 50% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVB", "short_name": "Near-poverty rate (<150% FPL)", "description": "Share of the population with income below 150% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVC", "short_name": "Low-income rate (<200% FPL)", "description": "Share of the population with income below 200% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_SNP", "short_name": "SNAP/food stamp participation rate", "description": "Share of households receiving SNAP (food stamp) benefits.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_VAL", @@ -10253,7 +11074,7 @@ "short_name": "No internet access rate", "description": "Share of households without any internet access.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INB", @@ -10281,42 +11102,42 @@ "short_name": "Income share: lowest quintile", "description": "Share of aggregate household income received by the lowest 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INM", "short_name": "Income share: second quintile", "description": "Share of aggregate household income received by the second 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INN", "short_name": "Income share: third quintile", "description": "Share of aggregate household income received by the middle 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INO", "short_name": "Income share: fourth quintile", "description": "Share of aggregate household income received by the fourth 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INP", "short_name": "Income share: highest quintile", "description": "Share of aggregate household income received by the highest 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INQ", "short_name": "Income share: top 5%", "description": "Share of aggregate household income received by the top 5% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_OWS", @@ -10330,63 +11151,63 @@ "short_name": "Limited English proficiency rate", "description": "Share of the population aged 5+ who speak English less than 'very well'.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_UNS", "short_name": "Uninsured rate", "description": "Share of the civilian noninstitutionalized population without health insurance.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_UMP", "short_name": "Unemployment rate", "description": "Share of the civilian labor force that is unemployed.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DIS", "short_name": "Disability rate", "description": "Share of the civilian noninstitutionalized population with any disability.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_MCR", "short_name": "Medicare coverage rate", "description": "Share of the civilian noninstitutionalized population covered by Medicare.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_MCD", "short_name": "Medicaid coverage rate", "description": "Share of the civilian noninstitutionalized population covered by Medicaid or other means-tested public insurance.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "census_ur_pct_urban_pop", "short_name": "Percent urban population", "description": "Share of county population residing in Census-defined urban areas.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "census_ur_pct_urban_land", "short_name": "Percent urban land area", "description": "Share of county land area within Census-defined urban areas.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "census_ur_pct_urban_hu", "short_name": "Percent urban housing units", "description": "Share of county housing units located in Census-defined urban areas.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" } ] }, @@ -10419,63 +11240,63 @@ "short_name": "Broadband internet subscription rate", "description": "Share of households with a broadband internet subscription.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_BTH", - "short_name": "Birth rate (women 15–50)", - "description": "Share of women aged 15–50 who gave birth in the past 12 months.", + "short_name": "Birth rate (women 1550)", + "description": "Share of women aged 1550 who gave birth in the past 12 months.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DCY", "short_name": "Opportunity youth rate", - "description": "Share of youth aged 16–24 who are neither enrolled in school nor employed.", + "description": "Share of youth aged 1624 who are neither enrolled in school nor employed.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_EDB", "short_name": "High school graduation rate", "description": "Share of adults aged 25+ who have at least a high school diploma or equivalent.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_EDC", "short_name": "Higher education attainment rate", "description": "Share of adults aged 25+ who have attended any college or higher.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_GNI", "short_name": "Gini income inequality index", "description": "Measure of household income inequality (0=perfect equality, 1=maximum inequality).", "measure_type": "Index", - "unit": "Index (0–1)" + "unit": "Index (01)" }, { "name": "acs_GRP", "short_name": "Group quarters rate", "description": "Share of the total population living in group quarters (prisons, dorms, nursing homes, etc.).", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HBS", "short_name": "Severe housing cost burden rate", "description": "Share of households spending 50% or more of income on housing costs.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HBU", "short_name": "Housing cost burden rate", "description": "Share of households spending 30% or more of income on housing costs.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_POP", @@ -10500,29 +11321,29 @@ }, { "name": "acs_POP_I", - "short_name": "Infant population (0–4 years)", - "description": "Total count of infants aged 0–4 years.", + "short_name": "Infant population (04 years)", + "description": "Total count of infants aged 04 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_J", - "short_name": "Juvenile population (5–17 years)", - "description": "Total count of children and adolescents aged 5–17 years.", + "short_name": "Juvenile population (517 years)", + "description": "Total count of children and adolescents aged 517 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_Y", - "short_name": "Young adult population (18–39 years)", - "description": "Total count of young adults aged 18–39 years.", + "short_name": "Young adult population (1839 years)", + "description": "Total count of young adults aged 1839 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_O", - "short_name": "Middle-aged adult population (40–64 years)", - "description": "Total count of middle-aged adults aged 40–64 years.", + "short_name": "Middle-aged adult population (4064 years)", + "description": "Total count of middle-aged adults aged 4064 years.", "measure_type": "Count", "unit": "Persons" }, @@ -10538,54 +11359,54 @@ "short_name": "Male share of population", "description": "Proportion of the population that is male.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_F", "short_name": "Female share of population", "description": "Proportion of the population that is female.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_I", - "short_name": "Infant share of population (0–4 years)", - "description": "Proportion of the population aged 0–4 years.", + "short_name": "Infant share of population (04 years)", + "description": "Proportion of the population aged 04 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_J", - "short_name": "Juvenile share of population (5–17 years)", - "description": "Proportion of the population aged 5–17 years.", + "short_name": "Juvenile share of population (517 years)", + "description": "Proportion of the population aged 517 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_Y", - "short_name": "Young adult share of population (18–39 years)", - "description": "Proportion of the population aged 18–39 years.", + "short_name": "Young adult share of population (1839 years)", + "description": "Proportion of the population aged 1839 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_O", - "short_name": "Middle-aged adult share of population (40–64 years)", - "description": "Proportion of the population aged 40–64 years.", + "short_name": "Middle-aged adult share of population (4064 years)", + "description": "Proportion of the population aged 4064 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_S", "short_name": "Senior share of population (65+ years)", "description": "Proportion of the population aged 65 years and older.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DEP", "short_name": "Age dependency ratio", - "description": "Ratio of dependents (ages 0–17 and 65+) to working-age adults (ages 18–64).", + "description": "Ratio of dependents (ages 017 and 65+) to working-age adults (ages 1864).", "measure_type": "Ratio", "unit": "Ratio" }, @@ -10643,140 +11464,140 @@ "short_name": "Non-Hispanic White share", "description": "Proportion of the population that is Non-Hispanic White.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_B", "short_name": "Non-Hispanic Black share", "description": "Proportion of the population that is Non-Hispanic Black or African American.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_P", "short_name": "Native American share", "description": "Proportion of the population that is Non-Hispanic American Indian and Alaska Native.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_A", "short_name": "Asian share", "description": "Proportion of the population that is Non-Hispanic Asian.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_P1", "short_name": "Pacific Islander/Native Hawaiian share", "description": "Proportion of the population that is Non-Hispanic Native Hawaiian and Other Pacific Islander.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_Q", "short_name": "Two or more races share", "description": "Proportion of the population identifying as Non-Hispanic two or more races.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_H", "short_name": "Hispanic or Latino share", "description": "Proportion of the population that is Hispanic or Latino.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_REX", "short_name": "Race-Ethnicity Diversity Index", "description": "Probability that two randomly chosen residents are from different racial/ethnic groups (0=no diversity, ~1=maximum diversity).", "measure_type": "Index", - "unit": "Index (0–1)" + "unit": "Index (01)" }, { "name": "acs_HTA", "short_name": "Single-parent household rate", "description": "Share of family households headed by a single parent with children.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HTJ", "short_name": "Crowded housing rate", "description": "Share of occupied housing units with more than 1 person per room.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUF", "short_name": "Incomplete plumbing rate", "description": "Share of housing units without complete indoor plumbing.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUG", "short_name": "No telephone service rate", "description": "Share of occupied housing units without telephone service.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUN", "short_name": "Mobile home rate", "description": "Share of housing units that are mobile homes or trailers.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUO", "short_name": "Owner-occupied housing rate", "description": "Share of occupied housing units that are owner-occupied.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_POV", "short_name": "Poverty rate", "description": "Share of the population with income below the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PUB", "short_name": "Public transit commute rate", "description": "Share of workers who commute primarily by public transportation.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVA", "short_name": "Deep poverty rate (<50% FPL)", "description": "Share of the population with income below 50% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVB", "short_name": "Near-poverty rate (<150% FPL)", "description": "Share of the population with income below 150% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVC", "short_name": "Low-income rate (<200% FPL)", "description": "Share of the population with income below 200% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_SNP", "short_name": "SNAP/food stamp participation rate", "description": "Share of households receiving SNAP (food stamp) benefits.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_VAL", @@ -10790,7 +11611,7 @@ "short_name": "No internet access rate", "description": "Share of households without any internet access.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INB", @@ -10818,42 +11639,42 @@ "short_name": "Income share: lowest quintile", "description": "Share of aggregate household income received by the lowest 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INM", "short_name": "Income share: second quintile", "description": "Share of aggregate household income received by the second 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INN", "short_name": "Income share: third quintile", "description": "Share of aggregate household income received by the middle 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INO", "short_name": "Income share: fourth quintile", "description": "Share of aggregate household income received by the fourth 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INP", "short_name": "Income share: highest quintile", "description": "Share of aggregate household income received by the highest 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INQ", "short_name": "Income share: top 5%", "description": "Share of aggregate household income received by the top 5% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_OWS", @@ -10867,42 +11688,42 @@ "short_name": "Limited English proficiency rate", "description": "Share of the population aged 5+ who speak English less than 'very well'.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_UNS", "short_name": "Uninsured rate", "description": "Share of the civilian noninstitutionalized population without health insurance.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_UMP", "short_name": "Unemployment rate", "description": "Share of the civilian labor force that is unemployed.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DIS", "short_name": "Disability rate", "description": "Share of the civilian noninstitutionalized population with any disability.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_MCR", "short_name": "Medicare coverage rate", "description": "Share of the civilian noninstitutionalized population covered by Medicare.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_MCD", "short_name": "Medicaid coverage rate", "description": "Share of the civilian noninstitutionalized population covered by Medicaid or other means-tested public insurance.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" } ] }, @@ -10935,63 +11756,63 @@ "short_name": "Broadband internet subscription rate", "description": "Share of households with a broadband internet subscription.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_BTH", - "short_name": "Birth rate (women 15–50)", - "description": "Share of women aged 15–50 who gave birth in the past 12 months.", + "short_name": "Birth rate (women 1550)", + "description": "Share of women aged 1550 who gave birth in the past 12 months.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DCY", "short_name": "Opportunity youth rate", - "description": "Share of youth aged 16–24 who are neither enrolled in school nor employed.", + "description": "Share of youth aged 1624 who are neither enrolled in school nor employed.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_EDB", "short_name": "High school graduation rate", "description": "Share of adults aged 25+ who have at least a high school diploma or equivalent.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_EDC", "short_name": "Higher education attainment rate", "description": "Share of adults aged 25+ who have attended any college or higher.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_GNI", "short_name": "Gini income inequality index", "description": "Measure of household income inequality (0=perfect equality, 1=maximum inequality).", "measure_type": "Index", - "unit": "Index (0–1)" + "unit": "Index (01)" }, { "name": "acs_GRP", "short_name": "Group quarters rate", "description": "Share of the total population living in group quarters (prisons, dorms, nursing homes, etc.).", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HBS", "short_name": "Severe housing cost burden rate", "description": "Share of households spending 50% or more of income on housing costs.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HBU", "short_name": "Housing cost burden rate", "description": "Share of households spending 30% or more of income on housing costs.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_POP", @@ -11016,29 +11837,29 @@ }, { "name": "acs_POP_I", - "short_name": "Infant population (0–4 years)", - "description": "Total count of infants aged 0–4 years.", + "short_name": "Infant population (04 years)", + "description": "Total count of infants aged 04 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_J", - "short_name": "Juvenile population (5–17 years)", - "description": "Total count of children and adolescents aged 5–17 years.", + "short_name": "Juvenile population (517 years)", + "description": "Total count of children and adolescents aged 517 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_Y", - "short_name": "Young adult population (18–39 years)", - "description": "Total count of young adults aged 18–39 years.", + "short_name": "Young adult population (1839 years)", + "description": "Total count of young adults aged 1839 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_O", - "short_name": "Middle-aged adult population (40–64 years)", - "description": "Total count of middle-aged adults aged 40–64 years.", + "short_name": "Middle-aged adult population (4064 years)", + "description": "Total count of middle-aged adults aged 4064 years.", "measure_type": "Count", "unit": "Persons" }, @@ -11054,54 +11875,54 @@ "short_name": "Male share of population", "description": "Proportion of the population that is male.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_F", "short_name": "Female share of population", "description": "Proportion of the population that is female.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_I", - "short_name": "Infant share of population (0–4 years)", - "description": "Proportion of the population aged 0–4 years.", + "short_name": "Infant share of population (04 years)", + "description": "Proportion of the population aged 04 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_J", - "short_name": "Juvenile share of population (5–17 years)", - "description": "Proportion of the population aged 5–17 years.", + "short_name": "Juvenile share of population (517 years)", + "description": "Proportion of the population aged 517 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_Y", - "short_name": "Young adult share of population (18–39 years)", - "description": "Proportion of the population aged 18–39 years.", + "short_name": "Young adult share of population (1839 years)", + "description": "Proportion of the population aged 1839 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_O", - "short_name": "Middle-aged adult share of population (40–64 years)", - "description": "Proportion of the population aged 40–64 years.", + "short_name": "Middle-aged adult share of population (4064 years)", + "description": "Proportion of the population aged 4064 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_S", "short_name": "Senior share of population (65+ years)", "description": "Proportion of the population aged 65 years and older.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DEP", "short_name": "Age dependency ratio", - "description": "Ratio of dependents (ages 0–17 and 65+) to working-age adults (ages 18–64).", + "description": "Ratio of dependents (ages 017 and 65+) to working-age adults (ages 1864).", "measure_type": "Ratio", "unit": "Ratio" }, @@ -11159,140 +11980,140 @@ "short_name": "Non-Hispanic White share", "description": "Proportion of the population that is Non-Hispanic White.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_B", "short_name": "Non-Hispanic Black share", "description": "Proportion of the population that is Non-Hispanic Black or African American.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_P", "short_name": "Native American share", "description": "Proportion of the population that is Non-Hispanic American Indian and Alaska Native.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_A", "short_name": "Asian share", "description": "Proportion of the population that is Non-Hispanic Asian.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_P1", "short_name": "Pacific Islander/Native Hawaiian share", "description": "Proportion of the population that is Non-Hispanic Native Hawaiian and Other Pacific Islander.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_Q", "short_name": "Two or more races share", "description": "Proportion of the population identifying as Non-Hispanic two or more races.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_H", "short_name": "Hispanic or Latino share", "description": "Proportion of the population that is Hispanic or Latino.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_REX", "short_name": "Race-Ethnicity Diversity Index", "description": "Probability that two randomly chosen residents are from different racial/ethnic groups (0=no diversity, ~1=maximum diversity).", "measure_type": "Index", - "unit": "Index (0–1)" + "unit": "Index (01)" }, { "name": "acs_HTA", "short_name": "Single-parent household rate", "description": "Share of family households headed by a single parent with children.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HTJ", "short_name": "Crowded housing rate", "description": "Share of occupied housing units with more than 1 person per room.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUF", "short_name": "Incomplete plumbing rate", "description": "Share of housing units without complete indoor plumbing.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUG", "short_name": "No telephone service rate", "description": "Share of occupied housing units without telephone service.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUN", "short_name": "Mobile home rate", "description": "Share of housing units that are mobile homes or trailers.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUO", "short_name": "Owner-occupied housing rate", "description": "Share of occupied housing units that are owner-occupied.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_POV", "short_name": "Poverty rate", "description": "Share of the population with income below the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PUB", "short_name": "Public transit commute rate", "description": "Share of workers who commute primarily by public transportation.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVA", "short_name": "Deep poverty rate (<50% FPL)", "description": "Share of the population with income below 50% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVB", "short_name": "Near-poverty rate (<150% FPL)", "description": "Share of the population with income below 150% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVC", "short_name": "Low-income rate (<200% FPL)", "description": "Share of the population with income below 200% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_SNP", "short_name": "SNAP/food stamp participation rate", "description": "Share of households receiving SNAP (food stamp) benefits.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_VAL", @@ -11306,7 +12127,7 @@ "short_name": "No internet access rate", "description": "Share of households without any internet access.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INB", @@ -11334,42 +12155,42 @@ "short_name": "Income share: lowest quintile", "description": "Share of aggregate household income received by the lowest 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INM", "short_name": "Income share: second quintile", "description": "Share of aggregate household income received by the second 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INN", "short_name": "Income share: third quintile", "description": "Share of aggregate household income received by the middle 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INO", "short_name": "Income share: fourth quintile", "description": "Share of aggregate household income received by the fourth 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INP", "short_name": "Income share: highest quintile", "description": "Share of aggregate household income received by the highest 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INQ", "short_name": "Income share: top 5%", "description": "Share of aggregate household income received by the top 5% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_OWS", @@ -11383,42 +12204,42 @@ "short_name": "Limited English proficiency rate", "description": "Share of the population aged 5+ who speak English less than 'very well'.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_UNS", "short_name": "Uninsured rate", "description": "Share of the civilian noninstitutionalized population without health insurance.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_UMP", "short_name": "Unemployment rate", "description": "Share of the civilian labor force that is unemployed.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DIS", "short_name": "Disability rate", "description": "Share of the civilian noninstitutionalized population with any disability.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_MCR", "short_name": "Medicare coverage rate", "description": "Share of the civilian noninstitutionalized population covered by Medicare.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_MCD", "short_name": "Medicaid coverage rate", "description": "Share of the civilian noninstitutionalized population covered by Medicaid or other means-tested public insurance.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" } ] }, @@ -11451,63 +12272,63 @@ "short_name": "Broadband internet subscription rate", "description": "Share of households with a broadband internet subscription.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_BTH", - "short_name": "Birth rate (women 15–50)", - "description": "Share of women aged 15–50 who gave birth in the past 12 months.", + "short_name": "Birth rate (women 1550)", + "description": "Share of women aged 1550 who gave birth in the past 12 months.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DCY", "short_name": "Opportunity youth rate", - "description": "Share of youth aged 16–24 who are neither enrolled in school nor employed.", + "description": "Share of youth aged 1624 who are neither enrolled in school nor employed.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_EDB", "short_name": "High school graduation rate", "description": "Share of adults aged 25+ who have at least a high school diploma or equivalent.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_EDC", "short_name": "Higher education attainment rate", "description": "Share of adults aged 25+ who have attended any college or higher.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_GNI", "short_name": "Gini income inequality index", "description": "Measure of household income inequality (0=perfect equality, 1=maximum inequality).", "measure_type": "Index", - "unit": "Index (0–1)" + "unit": "Index (01)" }, { "name": "acs_GRP", "short_name": "Group quarters rate", "description": "Share of the total population living in group quarters (prisons, dorms, nursing homes, etc.).", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HBS", "short_name": "Severe housing cost burden rate", "description": "Share of households spending 50% or more of income on housing costs.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HBU", "short_name": "Housing cost burden rate", "description": "Share of households spending 30% or more of income on housing costs.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_POP", @@ -11532,29 +12353,29 @@ }, { "name": "acs_POP_I", - "short_name": "Infant population (0–4 years)", - "description": "Total count of infants aged 0–4 years.", + "short_name": "Infant population (04 years)", + "description": "Total count of infants aged 04 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_J", - "short_name": "Juvenile population (5–17 years)", - "description": "Total count of children and adolescents aged 5–17 years.", + "short_name": "Juvenile population (517 years)", + "description": "Total count of children and adolescents aged 517 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_Y", - "short_name": "Young adult population (18–39 years)", - "description": "Total count of young adults aged 18–39 years.", + "short_name": "Young adult population (1839 years)", + "description": "Total count of young adults aged 1839 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_O", - "short_name": "Middle-aged adult population (40–64 years)", - "description": "Total count of middle-aged adults aged 40–64 years.", + "short_name": "Middle-aged adult population (4064 years)", + "description": "Total count of middle-aged adults aged 4064 years.", "measure_type": "Count", "unit": "Persons" }, @@ -11570,54 +12391,54 @@ "short_name": "Male share of population", "description": "Proportion of the population that is male.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_F", "short_name": "Female share of population", "description": "Proportion of the population that is female.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_I", - "short_name": "Infant share of population (0–4 years)", - "description": "Proportion of the population aged 0–4 years.", + "short_name": "Infant share of population (04 years)", + "description": "Proportion of the population aged 04 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_J", - "short_name": "Juvenile share of population (5–17 years)", - "description": "Proportion of the population aged 5–17 years.", + "short_name": "Juvenile share of population (517 years)", + "description": "Proportion of the population aged 517 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_Y", - "short_name": "Young adult share of population (18–39 years)", - "description": "Proportion of the population aged 18–39 years.", + "short_name": "Young adult share of population (1839 years)", + "description": "Proportion of the population aged 1839 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_O", - "short_name": "Middle-aged adult share of population (40–64 years)", - "description": "Proportion of the population aged 40–64 years.", + "short_name": "Middle-aged adult share of population (4064 years)", + "description": "Proportion of the population aged 4064 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_S", "short_name": "Senior share of population (65+ years)", "description": "Proportion of the population aged 65 years and older.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DEP", "short_name": "Age dependency ratio", - "description": "Ratio of dependents (ages 0–17 and 65+) to working-age adults (ages 18–64).", + "description": "Ratio of dependents (ages 017 and 65+) to working-age adults (ages 1864).", "measure_type": "Ratio", "unit": "Ratio" }, @@ -11675,140 +12496,140 @@ "short_name": "Non-Hispanic White share", "description": "Proportion of the population that is Non-Hispanic White.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_B", "short_name": "Non-Hispanic Black share", "description": "Proportion of the population that is Non-Hispanic Black or African American.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_P", "short_name": "Native American share", "description": "Proportion of the population that is Non-Hispanic American Indian and Alaska Native.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_A", "short_name": "Asian share", "description": "Proportion of the population that is Non-Hispanic Asian.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_P1", "short_name": "Pacific Islander/Native Hawaiian share", "description": "Proportion of the population that is Non-Hispanic Native Hawaiian and Other Pacific Islander.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_Q", "short_name": "Two or more races share", "description": "Proportion of the population identifying as Non-Hispanic two or more races.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_H", "short_name": "Hispanic or Latino share", "description": "Proportion of the population that is Hispanic or Latino.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_REX", "short_name": "Race-Ethnicity Diversity Index", "description": "Probability that two randomly chosen residents are from different racial/ethnic groups (0=no diversity, ~1=maximum diversity).", "measure_type": "Index", - "unit": "Index (0–1)" + "unit": "Index (01)" }, { "name": "acs_HTA", "short_name": "Single-parent household rate", "description": "Share of family households headed by a single parent with children.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HTJ", "short_name": "Crowded housing rate", "description": "Share of occupied housing units with more than 1 person per room.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUF", "short_name": "Incomplete plumbing rate", "description": "Share of housing units without complete indoor plumbing.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUG", "short_name": "No telephone service rate", "description": "Share of occupied housing units without telephone service.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUN", "short_name": "Mobile home rate", "description": "Share of housing units that are mobile homes or trailers.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUO", "short_name": "Owner-occupied housing rate", "description": "Share of occupied housing units that are owner-occupied.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_POV", "short_name": "Poverty rate", "description": "Share of the population with income below the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PUB", "short_name": "Public transit commute rate", "description": "Share of workers who commute primarily by public transportation.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVA", "short_name": "Deep poverty rate (<50% FPL)", "description": "Share of the population with income below 50% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVB", "short_name": "Near-poverty rate (<150% FPL)", "description": "Share of the population with income below 150% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVC", "short_name": "Low-income rate (<200% FPL)", "description": "Share of the population with income below 200% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_SNP", "short_name": "SNAP/food stamp participation rate", "description": "Share of households receiving SNAP (food stamp) benefits.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_VAL", @@ -11822,7 +12643,7 @@ "short_name": "No internet access rate", "description": "Share of households without any internet access.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INB", @@ -11850,42 +12671,42 @@ "short_name": "Income share: lowest quintile", "description": "Share of aggregate household income received by the lowest 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INM", "short_name": "Income share: second quintile", "description": "Share of aggregate household income received by the second 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INN", "short_name": "Income share: third quintile", "description": "Share of aggregate household income received by the middle 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INO", "short_name": "Income share: fourth quintile", "description": "Share of aggregate household income received by the fourth 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INP", "short_name": "Income share: highest quintile", "description": "Share of aggregate household income received by the highest 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INQ", "short_name": "Income share: top 5%", "description": "Share of aggregate household income received by the top 5% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_OWS", @@ -11899,42 +12720,42 @@ "short_name": "Limited English proficiency rate", "description": "Share of the population aged 5+ who speak English less than 'very well'.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_UNS", "short_name": "Uninsured rate", "description": "Share of the civilian noninstitutionalized population without health insurance.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_UMP", "short_name": "Unemployment rate", "description": "Share of the civilian labor force that is unemployed.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DIS", "short_name": "Disability rate", "description": "Share of the civilian noninstitutionalized population with any disability.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_MCR", "short_name": "Medicare coverage rate", "description": "Share of the civilian noninstitutionalized population covered by Medicare.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_MCD", "short_name": "Medicaid coverage rate", "description": "Share of the civilian noninstitutionalized population covered by Medicaid or other means-tested public insurance.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" } ] }, @@ -11967,63 +12788,63 @@ "short_name": "Broadband internet subscription rate", "description": "Share of households with a broadband internet subscription.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_BTH", - "short_name": "Birth rate (women 15–50)", - "description": "Share of women aged 15–50 who gave birth in the past 12 months.", + "short_name": "Birth rate (women 1550)", + "description": "Share of women aged 1550 who gave birth in the past 12 months.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DCY", "short_name": "Opportunity youth rate", - "description": "Share of youth aged 16–24 who are neither enrolled in school nor employed.", + "description": "Share of youth aged 1624 who are neither enrolled in school nor employed.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_EDB", "short_name": "High school graduation rate", "description": "Share of adults aged 25+ who have at least a high school diploma or equivalent.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_EDC", "short_name": "Higher education attainment rate", "description": "Share of adults aged 25+ who have attended any college or higher.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_GNI", "short_name": "Gini income inequality index", "description": "Measure of household income inequality (0=perfect equality, 1=maximum inequality).", "measure_type": "Index", - "unit": "Index (0–1)" + "unit": "Index (01)" }, { "name": "acs_GRP", "short_name": "Group quarters rate", "description": "Share of the total population living in group quarters (prisons, dorms, nursing homes, etc.).", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HBS", "short_name": "Severe housing cost burden rate", "description": "Share of households spending 50% or more of income on housing costs.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HBU", "short_name": "Housing cost burden rate", "description": "Share of households spending 30% or more of income on housing costs.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_POP", @@ -12048,29 +12869,29 @@ }, { "name": "acs_POP_I", - "short_name": "Infant population (0–4 years)", - "description": "Total count of infants aged 0–4 years.", + "short_name": "Infant population (04 years)", + "description": "Total count of infants aged 04 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_J", - "short_name": "Juvenile population (5–17 years)", - "description": "Total count of children and adolescents aged 5–17 years.", + "short_name": "Juvenile population (517 years)", + "description": "Total count of children and adolescents aged 517 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_Y", - "short_name": "Young adult population (18–39 years)", - "description": "Total count of young adults aged 18–39 years.", + "short_name": "Young adult population (1839 years)", + "description": "Total count of young adults aged 1839 years.", "measure_type": "Count", "unit": "Persons" }, { "name": "acs_POP_O", - "short_name": "Middle-aged adult population (40–64 years)", - "description": "Total count of middle-aged adults aged 40–64 years.", + "short_name": "Middle-aged adult population (4064 years)", + "description": "Total count of middle-aged adults aged 4064 years.", "measure_type": "Count", "unit": "Persons" }, @@ -12086,54 +12907,54 @@ "short_name": "Male share of population", "description": "Proportion of the population that is male.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_F", "short_name": "Female share of population", "description": "Proportion of the population that is female.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_I", - "short_name": "Infant share of population (0–4 years)", - "description": "Proportion of the population aged 0–4 years.", + "short_name": "Infant share of population (04 years)", + "description": "Proportion of the population aged 04 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_J", - "short_name": "Juvenile share of population (5–17 years)", - "description": "Proportion of the population aged 5–17 years.", + "short_name": "Juvenile share of population (517 years)", + "description": "Proportion of the population aged 517 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_Y", - "short_name": "Young adult share of population (18–39 years)", - "description": "Proportion of the population aged 18–39 years.", + "short_name": "Young adult share of population (1839 years)", + "description": "Proportion of the population aged 1839 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_O", - "short_name": "Middle-aged adult share of population (40–64 years)", - "description": "Proportion of the population aged 40–64 years.", + "short_name": "Middle-aged adult share of population (4064 years)", + "description": "Proportion of the population aged 4064 years.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_S", "short_name": "Senior share of population (65+ years)", "description": "Proportion of the population aged 65 years and older.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DEP", "short_name": "Age dependency ratio", - "description": "Ratio of dependents (ages 0–17 and 65+) to working-age adults (ages 18–64).", + "description": "Ratio of dependents (ages 017 and 65+) to working-age adults (ages 1864).", "measure_type": "Ratio", "unit": "Ratio" }, @@ -12191,140 +13012,140 @@ "short_name": "Non-Hispanic White share", "description": "Proportion of the population that is Non-Hispanic White.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_B", "short_name": "Non-Hispanic Black share", "description": "Proportion of the population that is Non-Hispanic Black or African American.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_P", "short_name": "Native American share", "description": "Proportion of the population that is Non-Hispanic American Indian and Alaska Native.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_A", "short_name": "Asian share", "description": "Proportion of the population that is Non-Hispanic Asian.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_P1", "short_name": "Pacific Islander/Native Hawaiian share", "description": "Proportion of the population that is Non-Hispanic Native Hawaiian and Other Pacific Islander.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_Q", "short_name": "Two or more races share", "description": "Proportion of the population identifying as Non-Hispanic two or more races.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PCT_H", "short_name": "Hispanic or Latino share", "description": "Proportion of the population that is Hispanic or Latino.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_REX", "short_name": "Race-Ethnicity Diversity Index", "description": "Probability that two randomly chosen residents are from different racial/ethnic groups (0=no diversity, ~1=maximum diversity).", "measure_type": "Index", - "unit": "Index (0–1)" + "unit": "Index (01)" }, { "name": "acs_HTA", "short_name": "Single-parent household rate", "description": "Share of family households headed by a single parent with children.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HTJ", "short_name": "Crowded housing rate", "description": "Share of occupied housing units with more than 1 person per room.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUF", "short_name": "Incomplete plumbing rate", "description": "Share of housing units without complete indoor plumbing.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUG", "short_name": "No telephone service rate", "description": "Share of occupied housing units without telephone service.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUN", "short_name": "Mobile home rate", "description": "Share of housing units that are mobile homes or trailers.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_HUO", "short_name": "Owner-occupied housing rate", "description": "Share of occupied housing units that are owner-occupied.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_POV", "short_name": "Poverty rate", "description": "Share of the population with income below the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PUB", "short_name": "Public transit commute rate", "description": "Share of workers who commute primarily by public transportation.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVA", "short_name": "Deep poverty rate (<50% FPL)", "description": "Share of the population with income below 50% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVB", "short_name": "Near-poverty rate (<150% FPL)", "description": "Share of the population with income below 150% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_PVC", "short_name": "Low-income rate (<200% FPL)", "description": "Share of the population with income below 200% of the federal poverty level.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_SNP", "short_name": "SNAP/food stamp participation rate", "description": "Share of households receiving SNAP (food stamp) benefits.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_VAL", @@ -12338,7 +13159,7 @@ "short_name": "No internet access rate", "description": "Share of households without any internet access.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INB", @@ -12366,42 +13187,42 @@ "short_name": "Income share: lowest quintile", "description": "Share of aggregate household income received by the lowest 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INM", "short_name": "Income share: second quintile", "description": "Share of aggregate household income received by the second 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INN", "short_name": "Income share: third quintile", "description": "Share of aggregate household income received by the middle 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INO", "short_name": "Income share: fourth quintile", "description": "Share of aggregate household income received by the fourth 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INP", "short_name": "Income share: highest quintile", "description": "Share of aggregate household income received by the highest 20% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_INQ", "short_name": "Income share: top 5%", "description": "Share of aggregate household income received by the top 5% of households.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_OWS", @@ -12415,42 +13236,42 @@ "short_name": "Limited English proficiency rate", "description": "Share of the population aged 5+ who speak English less than 'very well'.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_UNS", "short_name": "Uninsured rate", "description": "Share of the civilian noninstitutionalized population without health insurance.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_UMP", "short_name": "Unemployment rate", "description": "Share of the civilian labor force that is unemployed.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_DIS", "short_name": "Disability rate", "description": "Share of the civilian noninstitutionalized population with any disability.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_MCR", "short_name": "Medicare coverage rate", "description": "Share of the civilian noninstitutionalized population covered by Medicare.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" }, { "name": "acs_MCD", "short_name": "Medicaid coverage rate", "description": "Share of the civilian noninstitutionalized population covered by Medicaid or other means-tested public insurance.", "measure_type": "Percent", - "unit": "Proportion (0–1)" + "unit": "Proportion (01)" } ] } @@ -12462,7 +13283,7 @@ "description": "The Mapping Medicare Disparities (MMD) by Population Tool is an interactive map that displays chronic disease prevalence, costs, hospitalization, and preventive care utilization data for Medicare Fee-for-Service beneficiaries. Data are available at the national, state, and county levels, stratified by age, race/ethnicity, and sex. Condition prevalence rates are calculated using ICD-10 diagnosis codes in Medicare claims data, following the Chronic Conditions Warehouse (CCW) definitions. The tool covers over 30 chronic conditions including diabetes, hypertension, COPD, heart failure, and mental health conditions, as well as preventive service utilization metrics. Data are updated annually.", "standard_files": [ { - "filename": "data_state_county_age_by_race.csv.gz", + "filename": "data_state_county_age.csv.gz", "columns": [ { "name": "geography", @@ -12824,7 +13645,7 @@ ] }, { - "filename": "data_state_county_age_by_sex.csv.gz", + "filename": "data_state_county_age_by_race.csv.gz", "columns": [ { "name": "geography", @@ -13186,7 +14007,7 @@ ] }, { - "filename": "data_state_county_age.csv.gz", + "filename": "data_state_county_age_by_sex.csv.gz", "columns": [ { "name": "geography", @@ -13623,7 +14444,7 @@ { "name": "chr_adult_obesity", "short_name": "Adult Obesity", - "description": "Percentage of adults with BMI ≥ 30 (age-adjusted).", + "description": "Percentage of adults with BMI 30 (age-adjusted).", "measure_type": "Percent", "unit": "Percent" }, @@ -14839,7 +15660,7 @@ { "name": "chr_adult_obesity", "short_name": "Adult Obesity", - "description": "Percentage of adults with BMI ≥ 30 (age-adjusted).", + "description": "Percentage of adults with BMI 30 (age-adjusted).", "measure_type": "Percent", "unit": "Percent" }, @@ -16703,6 +17524,74 @@ } ] }, + "epic_gas": { + "name": "epic_gas", + "display_name": "Epic Gas", + "description": "Epic Cosmos is a collaborative research platform containing de-identified patient data from over 300 million patients across more than 1,600 hospitals and health systems using Epic electronic health record systems. Data is accessed via SlicerDicer, a self-service analytics tool. The dataset includes emergency department visits, diagnoses, immunizations, laboratory results, and other clinical data. Due to privacy protections, counts fewer than 10 are suppressed and imputed. Coverage extends across all U.S. states and territories. Note that county-level and city-level stratifications could differ markedly in total sample size due to high levels of missingness of county data in some states.", + "standard_files": [ + { + "filename": "data.csv.gz", + "columns": [ + { + "name": "geography", + "short_name": "Geography", + "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", + "measure_type": "identifier", + "unit": "FIPS code" + }, + { + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date" + }, + { + "name": "age", + "short_name": "Age Group", + "description": "Age group category", + "measure_type": "category", + "unit": "" + }, + { + "name": "epic_n_strep_throat", + "short_name": "Strep Throat Patients", + "description": "Quarterly count of patients with a strep throat diagnosis (J02.0, J03.00, J03.01).", + "measure_type": "Count", + "unit": "patients" + }, + { + "name": "epic_pct_strep_throat", + "short_name": "Strep Throat Percentage", + "description": "Quarterly percent of patients with a strep throat diagnosis (J02.0, J03.00, J03.01).", + "measure_type": "Percent", + "unit": "Percent" + }, + { + "name": "epic_strep_throat_suppressed_flag", + "short_name": "Suppressed flag: strep throat", + "description": "Indicates whether the strep throat numerator was suppressed and imputed; applies to both epic_n_strep_throat and epic_pct_strep_throat.", + "measure_type": "Binary", + "unit": "0/1" + }, + { + "name": "epic_n_patients", + "short_name": "Total Patients", + "description": "Quarterly total patient count used as the denominator for the strep throat percentage.", + "measure_type": "Count", + "unit": "patients" + }, + { + "name": "epic_n_patients_suppressed_flag", + "short_name": "Suppressed flag: total patients", + "description": "Indicates whether the total patient count was suppressed and imputed.", + "measure_type": "Binary", + "unit": "0/1" + } + ] + } + ] + }, "epic_health_alerts": { "name": "epic_health_alerts", "display_name": "Epic Health Alerts", @@ -17335,7 +18224,7 @@ "description": "Google Health Trends data accessed via the Google Health Trends API, processed and collected using Yale DISSC's gtrends_collection framework. The data represents the probability of a short search session including a specific health-related term within a geography and timeframe, multiplied by 10 million for readability. Search volumes are provided at the DMA (Designated Market Area) and state level on a weekly basis. This data source enables tracking of public interest in health topics such as RSV, overdose, and naloxone as potential early indicators of disease activity or public health concerns.", "standard_files": [ { - "filename": "data_dma_year.csv.gz", + "filename": "data.csv.gz", "columns": [ { "name": "geography", @@ -17352,65 +18241,65 @@ "unit": "date" }, { - "name": "gtrends_drug+overdose", - "short_name": "Google Search Volume: Drug Overdose", - "description": "Google search volume for the term drug overdose.", + "name": "gtrends_rsv_vaccine", + "short_name": "Google Search Volume: rsv_vaccine", + "description": "Google search volume of the term rsv_vaccine.", "measure_type": "probability", "unit": "probability * 10M" }, { - "name": "gtrends_naloxone", - "short_name": "Google Search Volume: naloxone", - "description": "Google search volume of the term naloxone.", + "name": "gtrends_9mm", + "short_name": "Google Search Volume: 9mm", + "description": "Google search volume for the term 9mm.", "measure_type": "probability", "unit": "probability * 10M" }, { - "name": "gtrends_narcan", - "short_name": "Google Search Volume: narcan", - "description": "Google search volume of the term narcan.", + "name": "gtrends_naloxone", + "short_name": "Google Search Volume: naloxone", + "description": "Google search volume of the term naloxone.", "measure_type": "probability", "unit": "probability * 10M" }, { - "name": "gtrends_overdose", - "short_name": "Google Search Volume: overdose", - "description": "Google search volume of the term overdose.", + "name": "gtrends_drug+overdose", + "short_name": "Google Search Volume: Drug Overdose", + "description": "Google search volume for the term drug overdose.", "measure_type": "probability", "unit": "probability * 10M" }, { - "name": "gtrends_rsv_vaccine", - "short_name": "Google Search Volume: rsv_vaccine", - "description": "Google search volume of the term rsv_vaccine.", + "name": "gtrends_heat+exhaustion", + "short_name": "Google Search Volume: Heat Exhaustion", + "description": "Google search volume for the term heat exhaustion.", "measure_type": "probability", "unit": "probability * 10M" }, { - "name": "gtrends_rsv", - "short_name": "Google Search Volume: rsv", - "description": "Google search volume of the term rsv.", + "name": "gtrends_heat+stroke", + "short_name": "Google Search Volume: Heat Stroke", + "description": "Google search volume for the term heat stroke.", "measure_type": "probability", "unit": "probability * 10M" }, { - "name": "gtrends_heat+exhaustion", - "short_name": "Google Search Volume: Heat Exhaustion", - "description": "Google search volume for the term heat exhaustion.", + "name": "gtrends_narcan", + "short_name": "Google Search Volume: narcan", + "description": "Google search volume of the term narcan.", "measure_type": "probability", "unit": "probability * 10M" }, { - "name": "gtrends_heat+stroke", - "short_name": "Google Search Volume: Heat Stroke", - "description": "Google search volume for the term heat stroke.", + "name": "gtrends_overdose", + "short_name": "Google Search Volume: overdose", + "description": "Google search volume of the term overdose.", "measure_type": "probability", "unit": "probability * 10M" }, { - "name": "gtrends_9mm", - "short_name": "Google Search Volume: 9mm", - "description": "Google search volume for the term 9mm.", + "name": "gtrends_rsv", + "short_name": "Google Search Volume: rsv", + "description": "Google search volume of the term rsv.", "measure_type": "probability", "unit": "probability * 10M" }, @@ -17420,6 +18309,13 @@ "description": "Google search volume for the term shotgun.", "measure_type": "probability", "unit": "probability * 10M" + }, + { + "name": "gtrends_rsv_adjusted", + "short_name": "Google Search Volume: rsv_adjusted", + "description": "Google search volume of the term rsv_adjusted.", + "measure_type": "probability", + "unit": "probability * 10M" } ] }, @@ -17513,7 +18409,7 @@ ] }, { - "filename": "data_year.csv.gz", + "filename": "data_dma_year.csv.gz", "columns": [ { "name": "geography", @@ -17529,27 +18425,6 @@ "measure_type": "date", "unit": "date" }, - { - "name": "gtrends_rsv_vaccine", - "short_name": "Google Search Volume: rsv_vaccine", - "description": "Google search volume of the term rsv_vaccine.", - "measure_type": "probability", - "unit": "probability * 10M" - }, - { - "name": "gtrends_9mm", - "short_name": "Google Search Volume: 9mm", - "description": "Google search volume for the term 9mm.", - "measure_type": "probability", - "unit": "probability * 10M" - }, - { - "name": "gtrends_naloxone", - "short_name": "Google Search Volume: naloxone", - "description": "Google search volume of the term naloxone.", - "measure_type": "probability", - "unit": "probability * 10M" - }, { "name": "gtrends_drug+overdose", "short_name": "Google Search Volume: Drug Overdose", @@ -17558,16 +18433,9 @@ "unit": "probability * 10M" }, { - "name": "gtrends_heat+exhaustion", - "short_name": "Google Search Volume: Heat Exhaustion", - "description": "Google search volume for the term heat exhaustion.", - "measure_type": "probability", - "unit": "probability * 10M" - }, - { - "name": "gtrends_heat+stroke", - "short_name": "Google Search Volume: Heat Stroke", - "description": "Google search volume for the term heat stroke.", + "name": "gtrends_naloxone", + "short_name": "Google Search Volume: naloxone", + "description": "Google search volume of the term naloxone.", "measure_type": "probability", "unit": "probability * 10M" }, @@ -17585,6 +18453,13 @@ "measure_type": "probability", "unit": "probability * 10M" }, + { + "name": "gtrends_rsv_vaccine", + "short_name": "Google Search Volume: rsv_vaccine", + "description": "Google search volume of the term rsv_vaccine.", + "measure_type": "probability", + "unit": "probability * 10M" + }, { "name": "gtrends_rsv", "short_name": "Google Search Volume: rsv", @@ -17593,23 +18468,37 @@ "unit": "probability * 10M" }, { - "name": "gtrends_shotgun", - "short_name": "Google Search Volume: Shotgun", - "description": "Google search volume for the term shotgun.", + "name": "gtrends_heat+exhaustion", + "short_name": "Google Search Volume: Heat Exhaustion", + "description": "Google search volume for the term heat exhaustion.", "measure_type": "probability", "unit": "probability * 10M" }, { - "name": "gtrends_rsv_adjusted", - "short_name": "Google Search Volume: rsv_adjusted", - "description": "Google search volume of the term rsv_adjusted.", + "name": "gtrends_heat+stroke", + "short_name": "Google Search Volume: Heat Stroke", + "description": "Google search volume for the term heat stroke.", + "measure_type": "probability", + "unit": "probability * 10M" + }, + { + "name": "gtrends_9mm", + "short_name": "Google Search Volume: 9mm", + "description": "Google search volume for the term 9mm.", + "measure_type": "probability", + "unit": "probability * 10M" + }, + { + "name": "gtrends_shotgun", + "short_name": "Google Search Volume: Shotgun", + "description": "Google search volume for the term shotgun.", "measure_type": "probability", "unit": "probability * 10M" } ] }, { - "filename": "data.csv.gz", + "filename": "data_year.csv.gz", "columns": [ { "name": "geography", @@ -17853,7 +18742,7 @@ "description": "The Johns Hopkins University Measles Tracking Team compiles laboratory-confirmed measles case data from official state and county health department reports across the United States. The team aggregates data from 37+ jurisdictions, providing both state-level weekly summaries (using rash onset dates when available) and county-level daily case counts (based on official reporting dates). Data is updated on Tuesdays and Fridays at approximately 5:00 PM Eastern Time. The tracking effort was established in response to the 2025 measles outbreak to provide timely, granular geographic data on measles transmission. All data is released under CC BY 4.0 license with attribution required.", "standard_files": [ { - "filename": "data_county.csv.gz", + "filename": "data.csv.gz", "columns": [ { "name": "geography", @@ -17879,7 +18768,7 @@ ] }, { - "filename": "data_state.csv.gz", + "filename": "data_county.csv.gz", "columns": [ { "name": "geography", @@ -17905,7 +18794,7 @@ ] }, { - "filename": "data.csv.gz", + "filename": "data_state.csv.gz", "columns": [ { "name": "geography", @@ -17935,7 +18824,7 @@ "medicaid_quality": { "name": "medicaid_quality", "display_name": "Medicaid Quality", - "description": "Annual state-level performance data on the Medicaid and CHIP Adult Core Set and Child Core Set quality measures, as voluntarily reported by states to CMS and analyzed by Mathematica via the Quality Measure Reporting (QMR) system. Measures span behavioral health (e.g., follow-up after ED visits for mental illness, substance use disorder treatment), primary and preventive care (e.g., well-child visits, immunizations), maternal and perinatal health (e.g., prenatal and postpartum care, low birthweight), dental health, care of chronic conditions (e.g., diabetes, asthma, hypertension), and long-term services and supports. Each annual dataset includes state rates and national 25th and 75th percentile benchmarks. Data cover federal fiscal years 2014–2023. Reporting is voluntary; not all states report all measures each year. The wide-format standard file contains one row per state-year-payer-domain combination, with each measure-statistic combination as a separate column following the naming convention medicaid_{measure_abbr}_{population}_{sub_metric}_{stat} where population is 'ch' (child) or 'ad' (adult), sub_metric captures time windows or sub-components, and stat is 'rate', 'pct_25', or 'pct_75'.", + "description": "Annual state-level performance data on the Medicaid and CHIP Adult Core Set and Child Core Set quality measures, as voluntarily reported by states to CMS and analyzed by Mathematica via the Quality Measure Reporting (QMR) system. Measures span behavioral health (e.g., follow-up after ED visits for mental illness, substance use disorder treatment), primary and preventive care (e.g., well-child visits, immunizations), maternal and perinatal health (e.g., prenatal and postpartum care, low birthweight), dental health, care of chronic conditions (e.g., diabetes, asthma, hypertension), and long-term services and supports. Each annual dataset includes state rates and national 25th and 75th percentile benchmarks. Data cover federal fiscal years 20142023. Reporting is voluntary; not all states report all measures each year. The wide-format standard file contains one row per state-year-payer-domain combination, with each measure-statistic combination as a separate column following the naming convention medicaid_{measure_abbr}_{population}_{sub_metric}_{stat} where population is 'ch' (child) or 'ad' (adult), sub_metric captures time windows or sub-components, and stat is 'rate', 'pct_25', or 'pct_75'.", "standard_files": [ { "filename": "data.csv.gz", @@ -18082,8 +18971,8 @@ }, { "name": "medicaid_w34_ch_rate", - "short_name": "W34: Well-Child Visits Ages 3–4", - "description": "Percent of children ages 3–4 who had at least one well-child visit.", + "short_name": "W34: Well-Child Visits Ages 34", + "description": "Percent of children ages 34 who had at least one well-child visit.", "measure_type": "Percent", "unit": "Percent" }, @@ -18103,7 +18992,7 @@ }, { "name": "medicaid_ldl_ad_rate", - "short_name": "LDL: Comprehensive Diabetes Care – LDL-C Screening (Adult)", + "short_name": "LDL: Comprehensive Diabetes Care LDL-C Screening (Adult)", "description": "Percent of adults with diabetes who received an LDL-C screening.", "measure_type": "Percent", "unit": "Percent" @@ -18166,7 +19055,7 @@ }, { "name": "medicaid_amb_ch_rate", - "short_name": "AMB: Ambulatory Care – ED Visits (Child)", + "short_name": "AMB: Ambulatory Care ED Visits (Child)", "description": "Rate of emergency department visits among children per 1,000 member months.", "measure_type": "Rate", "unit": "Visits per 1,000 member months" @@ -18335,7 +19224,7 @@ { "name": "medicaid_bcs_ad_rate", "short_name": "BCS: Breast Cancer Screening (Adult)", - "description": "Percent of women aged 50–74 who received a mammogram for breast cancer screening.", + "description": "Percent of women aged 5074 who received a mammogram for breast cancer screening.", "measure_type": "Percent", "unit": "Percent" }, @@ -18356,7 +19245,7 @@ { "name": "medicaid_ccs_ad_rate", "short_name": "CCS: Cervical Cancer Screening (Adult)", - "description": "Percent of women aged 21–64 who received appropriate cervical cancer screening.", + "description": "Percent of women aged 2164 who received appropriate cervical cancer screening.", "measure_type": "Percent", "unit": "Percent" }, @@ -18586,7 +19475,7 @@ }, { "name": "medicaid_ha1c_ad_rate", - "short_name": "HA1C: Comprehensive Diabetes Care – HbA1c Testing (Adult, Alternate)", + "short_name": "HA1C: Comprehensive Diabetes Care HbA1c Testing (Adult, Alternate)", "description": "Percent of adults with diabetes who received an HbA1c test (alternate measure).", "measure_type": "Percent", "unit": "Percent" @@ -19006,7 +19895,7 @@ }, { "name": "medicaid_ccp_ch_rate", - "short_name": "CCP: Contraceptive Care – All Women (Child)", + "short_name": "CCP: Contraceptive Care All Women (Child)", "description": "Percent of adolescent females who received a most effective or moderately effective contraceptive method.", "measure_type": "Percent", "unit": "Percent" @@ -19090,7 +19979,7 @@ }, { "name": "medicaid_ccp_ad_rate", - "short_name": "CCP: Contraceptive Care – All Women (Adult)", + "short_name": "CCP: Contraceptive Care All Women (Adult)", "description": "Percent of adult women who received a most effective or moderately effective contraceptive method.", "measure_type": "Percent", "unit": "Percent" @@ -19237,7 +20126,7 @@ }, { "name": "medicaid_apm_ch_gluc_rate", - "short_name": "APM: Metabolic Monitoring on Antipsychotics – Blood Glucose (Child)", + "short_name": "APM: Metabolic Monitoring on Antipsychotics Blood Glucose (Child)", "description": "Percent of children on antipsychotics who received blood glucose monitoring.", "measure_type": "Percent", "unit": "Percent" @@ -19258,7 +20147,7 @@ }, { "name": "medicaid_apm_ch_chol_rate", - "short_name": "APM: Metabolic Monitoring on Antipsychotics – Cholesterol (Child)", + "short_name": "APM: Metabolic Monitoring on Antipsychotics Cholesterol (Child)", "description": "Percent of children on antipsychotics who received cholesterol monitoring.", "measure_type": "Percent", "unit": "Percent" @@ -19279,7 +20168,7 @@ }, { "name": "medicaid_apm_ch_gluc_chol_rate", - "short_name": "APM: Metabolic Monitoring on Antipsychotics – Blood Glucose and Cholesterol (Child)", + "short_name": "APM: Metabolic Monitoring on Antipsychotics Blood Glucose and Cholesterol (Child)", "description": "Percent of children on antipsychotics who received both blood glucose and cholesterol monitoring.", "measure_type": "Percent", "unit": "Percent" @@ -19321,7 +20210,7 @@ }, { "name": "medicaid_ccw_ad_rate", - "short_name": "CCW: Comprehensive Diabetes Care – HbA1c Testing (Adult)", + "short_name": "CCW: Comprehensive Diabetes Care HbA1c Testing (Adult)", "description": "Percent of adults with diabetes who received an HbA1c test.", "measure_type": "Percent", "unit": "Percent" @@ -19657,7 +20546,7 @@ }, { "name": "medicaid_cpc_ch_rate", - "short_name": "CPC: Contraceptive Care – Postpartum (Child)", + "short_name": "CPC: Contraceptive Care Postpartum (Child)", "description": "Percent of adolescent females with a live birth who received postpartum contraceptive care.", "measure_type": "Percent", "unit": "Percent" @@ -19699,7 +20588,7 @@ }, { "name": "medicaid_amm_ad_cont_rate", - "short_name": "AMM: Antidepressant Medication Management – Continuation (Adult)", + "short_name": "AMM: Antidepressant Medication Management Continuation (Adult)", "description": "Percent of adults with new depression who continued antidepressant medication for at least 180 days.", "measure_type": "Percent", "unit": "Percent" @@ -19741,7 +20630,7 @@ }, { "name": "medicaid_cpa_ad_rate", - "short_name": "CPA: Contraceptive Care – Postpartum (Adult)", + "short_name": "CPA: Contraceptive Care Postpartum (Adult)", "description": "Percent of adult women with a live birth who received postpartum contraceptive care.", "measure_type": "Percent", "unit": "Percent" @@ -19763,7 +20652,7 @@ { "name": "medicaid_col_ad_rate", "short_name": "COL: Colorectal Cancer Screening (Adult)", - "description": "Percent of adults aged 50–75 who received appropriate colorectal cancer screening.", + "description": "Percent of adults aged 5075 who received appropriate colorectal cancer screening.", "measure_type": "Percent", "unit": "Percent" }, @@ -19995,14 +20884,14 @@ "short_name": "MIC50", "description": "Median MIC value across isolates tested for a specific antimicrobial", "measure_type": "Concentration", - "unit": "µg/mL" + "unit": "g/mL" }, { "name": "mic90", "short_name": "MIC90", "description": "90th percentile MIC value across isolates tested for a specific antimicrobial", "measure_type": "Concentration", - "unit": "µg/mL" + "unit": "g/mL" } ] }, @@ -20098,14 +20987,14 @@ "short_name": "MIC50", "description": "Median MIC value across isolates tested for a specific antimicrobial", "measure_type": "Concentration", - "unit": "µg/mL" + "unit": "g/mL" }, { "name": "mic90", "short_name": "MIC90", "description": "90th percentile MIC value across isolates tested for a specific antimicrobial", "measure_type": "Concentration", - "unit": "µg/mL" + "unit": "g/mL" } ] }, @@ -20330,14 +21219,14 @@ "short_name": "MIC50", "description": "Median MIC value across isolates tested for a specific antimicrobial", "measure_type": "Concentration", - "unit": "µg/mL" + "unit": "g/mL" }, { "name": "mic90", "short_name": "MIC90", "description": "90th percentile MIC value across isolates tested for a specific antimicrobial", "measure_type": "Concentration", - "unit": "µg/mL" + "unit": "g/mL" } ] } @@ -20823,309 +21712,103 @@ { "name": "nccr_germ_cell_tumors_non_malignant_ucl", "short_name": "X. Germ Cell Tumors (Non-Malignant)", - "description": "Upper bound of the 95% confidence interval for the incidence rate of X. Germ Cell Tumors (Non-Malignant).", - "measure_type": "Incidence", - "unit": "Cases per 1,000,000" - }, - { - "name": "nccr_germ_cell_tumors_non_malignant_suppressed", - "short_name": "X. Germ Cell Tumors (Non-Malignant)", - "description": "Indicates whether the X. Germ Cell Tumors (Non-Malignant) incidence rate was suppressed (reported as 0 with no confidence interval).", - "measure_type": "Incidence", - "unit": "Cases per 1,000,000" - }, - { - "name": "nccr_germ_cell_tumors_non_malignant_not_collected", - "short_name": "X. Germ Cell Tumors (Non-Malignant)", - "description": "Indicates whether the X. Germ Cell Tumors (Non-Malignant) incidence rate was absent from the API response.", - "measure_type": "Incidence", - "unit": "Cases per 1,000,000" - }, - { - "name": "nccr_epithelial_neoplasms_and_melanomas", - "short_name": "XI. Epithelial Neoplasms And Melanomas", - "description": "Age-adjusted incidence rate of XI. Epithelial Neoplasms And Melanomas among children, adolescents, and young adults (ages 0-39).", - "measure_type": "Incidence", - "unit": "Cases per 1,000,000" - }, - { - "name": "nccr_epithelial_neoplasms_and_melanomas_lcl", - "short_name": "XI. Epithelial Neoplasms And Melanomas", - "description": "Lower bound of the 95% confidence interval for the incidence rate of XI. Epithelial Neoplasms And Melanomas.", - "measure_type": "Incidence", - "unit": "Cases per 1,000,000" - }, - { - "name": "nccr_epithelial_neoplasms_and_melanomas_ucl", - "short_name": "XI. Epithelial Neoplasms And Melanomas", - "description": "Upper bound of the 95% confidence interval for the incidence rate of XI. Epithelial Neoplasms And Melanomas.", - "measure_type": "Incidence", - "unit": "Cases per 1,000,000" - }, - { - "name": "nccr_epithelial_neoplasms_and_melanomas_suppressed", - "short_name": "XI. Epithelial Neoplasms And Melanomas", - "description": "Indicates whether the XI. Epithelial Neoplasms And Melanomas incidence rate was suppressed (reported as 0 with no confidence interval).", - "measure_type": "Incidence", - "unit": "Cases per 1,000,000" - }, - { - "name": "nccr_epithelial_neoplasms_and_melanomas_not_collected", - "short_name": "XI. Epithelial Neoplasms And Melanomas", - "description": "Indicates whether the XI. Epithelial Neoplasms And Melanomas incidence rate was absent from the API response.", - "measure_type": "Incidence", - "unit": "Cases per 1,000,000" - }, - { - "name": "nccr_neoplasms_other_and_nos", - "short_name": "XII. Other/ Unspecified Neoplasms", - "description": "Age-adjusted incidence rate of XII. Other/ Unspecified Neoplasms among children, adolescents, and young adults (ages 0-39).", - "measure_type": "Incidence", - "unit": "Cases per 1,000,000" - }, - { - "name": "nccr_neoplasms_other_and_nos_lcl", - "short_name": "XII. Other/ Unspecified Neoplasms", - "description": "Lower bound of the 95% confidence interval for the incidence rate of XII. Other/ Unspecified Neoplasms.", - "measure_type": "Incidence", - "unit": "Cases per 1,000,000" - }, - { - "name": "nccr_neoplasms_other_and_nos_ucl", - "short_name": "XII. Other/ Unspecified Neoplasms", - "description": "Upper bound of the 95% confidence interval for the incidence rate of XII. Other/ Unspecified Neoplasms.", - "measure_type": "Incidence", - "unit": "Cases per 1,000,000" - }, - { - "name": "nccr_neoplasms_other_and_nos_suppressed", - "short_name": "XII. Other/ Unspecified Neoplasms", - "description": "Indicates whether the XII. Other/ Unspecified Neoplasms incidence rate was suppressed (reported as 0 with no confidence interval).", - "measure_type": "Incidence", - "unit": "Cases per 1,000,000" - }, - { - "name": "nccr_neoplasms_other_and_nos_not_collected", - "short_name": "XII. Other/ Unspecified Neoplasms", - "description": "Indicates whether the XII. Other/ Unspecified Neoplasms incidence rate was absent from the API response.", - "measure_type": "Incidence", - "unit": "Cases per 1,000,000" - } - ] - } - ] - }, - "nchs_mortality": { - "name": "nchs_mortality", - "display_name": "NCHS Mortality", - "description": "The National Center for Health Statistics (NCHS) houses the the Vital Statistics Rapid Release (VSRR) program. The program reports monthly deaths from drug overdose at the state level and quarterly deaths from drug overdose at the county level, as well as quarterly age-adjusted mortality rates for 21 selected causes of death at the state level. Rates are expressed as per 100,000 people. Counts of 1–9 deaths are suppressed to protect privacy and imputed as 5; the suppressed_flag column identifies these records. Data from the VSSR program and are provisional, meaning they are subject to revision as more death certificates are received and processed. New York City and New York State are combined.", - "standard_files": [ - { - "filename": "data_county.csv.gz", - "columns": [ - { - "name": "geography", - "short_name": "Geography", - "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", - "measure_type": "identifier", - "unit": "FIPS code" - }, - { - "name": "time", - "short_name": "Time", - "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", - "measure_type": "date", - "unit": "date" - }, - { - "name": "n_deaths_overdose", - "short_name": "Drug overdose deaths", - "description": "Provisional count of drug overdose deaths. State-level data are 12-month rolling totals; county-level data are monthly.", - "measure_type": "Count", - "unit": "Deaths" - }, - { - "name": "suppressed", - "short_name": "Drug overdose suppression flag", - "description": "Indicates whether the county drug overdose death count was suppressed by NCHS. Due to privacy protections, counts fewer than 10 are suppressed and imputed to be 5.", - "measure_type": "Binary", - "unit": "Binary indicator" - }, - { - "name": "pct_pending_invest", - "short_name": "Percent pending investigation", - "description": "Percentage of death records still pending investigation for the reporting period.", - "measure_type": "Percent", - "unit": "Percent" - } - ] - }, - { - "filename": "data_state_21_causes.csv.gz", - "columns": [ - { - "name": "geography", - "short_name": "Geography", - "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", - "measure_type": "identifier", - "unit": "FIPS code" - }, - { - "name": "time", - "short_name": "Time", - "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", - "measure_type": "date", - "unit": "date" - }, - { - "name": "rate_all_causes", - "short_name": "All-cause mortality rate", - "description": "Quarterly age-adjusted death rate from all causes per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" - }, - { - "name": "rate_alzheimer_disease", - "short_name": "Alzheimer's mortality rate", - "description": "Quarterly age-adjusted death rate from Alzheimer's disease per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" - }, - { - "name": "rate_covid_19", - "short_name": "COVID-19 mortality rate", - "description": "Quarterly age-adjusted death rate from COVID-19 per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" - }, - { - "name": "rate_cancer", - "short_name": "Cancer mortality rate", - "description": "Quarterly age-adjusted death rate from cancer per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" - }, - { - "name": "rate_chronic_liver_disease_and_cirrhosis", - "short_name": "Liver disease mortality rate", - "description": "Quarterly age-adjusted death rate from chronic liver disease and cirrhosis per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" - }, - { - "name": "rate_chronic_lower_respiratory_diseases", - "short_name": "CLRD mortality rate", - "description": "Quarterly age-adjusted death rate from chronic lower respiratory diseases per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" - }, - { - "name": "rate_diabetes", - "short_name": "Diabetes mortality rate", - "description": "Quarterly age-adjusted death rate from diabetes per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" - }, - { - "name": "rate_drug_overdose", - "short_name": "Drug overdose mortality rate", - "description": "Quarterly age-adjusted death rate from drug overdose per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" - }, - { - "name": "rate_falls_ages_65_and_over", - "short_name": "Falls mortality rate (65+)", - "description": "Quarterly age-adjusted death rate from falls among adults 65 and over per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" + "description": "Upper bound of the 95% confidence interval for the incidence rate of X. Germ Cell Tumors (Non-Malignant).", + "measure_type": "Incidence", + "unit": "Cases per 1,000,000" }, { - "name": "rate_firearm_related_injury", - "short_name": "Firearm injury mortality rate", - "description": "Quarterly age-adjusted death rate from firearm-related injuries per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" + "name": "nccr_germ_cell_tumors_non_malignant_suppressed", + "short_name": "X. Germ Cell Tumors (Non-Malignant)", + "description": "Indicates whether the X. Germ Cell Tumors (Non-Malignant) incidence rate was suppressed (reported as 0 with no confidence interval).", + "measure_type": "Incidence", + "unit": "Cases per 1,000,000" }, { - "name": "rate_heart_disease", - "short_name": "Heart disease mortality rate", - "description": "Quarterly age-adjusted death rate from heart disease per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" + "name": "nccr_germ_cell_tumors_non_malignant_not_collected", + "short_name": "X. Germ Cell Tumors (Non-Malignant)", + "description": "Indicates whether the X. Germ Cell Tumors (Non-Malignant) incidence rate was absent from the API response.", + "measure_type": "Incidence", + "unit": "Cases per 1,000,000" }, { - "name": "rate_hiv_disease", - "short_name": "HIV mortality rate", - "description": "Quarterly age-adjusted death rate from HIV disease per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" + "name": "nccr_epithelial_neoplasms_and_melanomas", + "short_name": "XI. Epithelial Neoplasms And Melanomas", + "description": "Age-adjusted incidence rate of XI. Epithelial Neoplasms And Melanomas among children, adolescents, and young adults (ages 0-39).", + "measure_type": "Incidence", + "unit": "Cases per 1,000,000" }, { - "name": "rate_homicide", - "short_name": "Homicide mortality rate", - "description": "Quarterly age-adjusted death rate from homicide per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" + "name": "nccr_epithelial_neoplasms_and_melanomas_lcl", + "short_name": "XI. Epithelial Neoplasms And Melanomas", + "description": "Lower bound of the 95% confidence interval for the incidence rate of XI. Epithelial Neoplasms And Melanomas.", + "measure_type": "Incidence", + "unit": "Cases per 1,000,000" }, { - "name": "rate_hypertension", - "short_name": "Hypertension mortality rate", - "description": "Quarterly age-adjusted death rate from hypertension per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" + "name": "nccr_epithelial_neoplasms_and_melanomas_ucl", + "short_name": "XI. Epithelial Neoplasms And Melanomas", + "description": "Upper bound of the 95% confidence interval for the incidence rate of XI. Epithelial Neoplasms And Melanomas.", + "measure_type": "Incidence", + "unit": "Cases per 1,000,000" }, { - "name": "rate_influenza_and_pneumonia", - "short_name": "Flu & pneumonia mortality rate", - "description": "Quarterly age-adjusted death rate from influenza and pneumonia per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" + "name": "nccr_epithelial_neoplasms_and_melanomas_suppressed", + "short_name": "XI. Epithelial Neoplasms And Melanomas", + "description": "Indicates whether the XI. Epithelial Neoplasms And Melanomas incidence rate was suppressed (reported as 0 with no confidence interval).", + "measure_type": "Incidence", + "unit": "Cases per 1,000,000" }, { - "name": "rate_kidney_disease", - "short_name": "Kidney disease mortality rate", - "description": "Quarterly age-adjusted death rate from kidney disease per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" + "name": "nccr_epithelial_neoplasms_and_melanomas_not_collected", + "short_name": "XI. Epithelial Neoplasms And Melanomas", + "description": "Indicates whether the XI. Epithelial Neoplasms And Melanomas incidence rate was absent from the API response.", + "measure_type": "Incidence", + "unit": "Cases per 1,000,000" }, { - "name": "rate_parkinson_disease", - "short_name": "Parkinson's mortality rate", - "description": "Quarterly age-adjusted death rate from Parkinson's disease per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" + "name": "nccr_neoplasms_other_and_nos", + "short_name": "XII. Other/ Unspecified Neoplasms", + "description": "Age-adjusted incidence rate of XII. Other/ Unspecified Neoplasms among children, adolescents, and young adults (ages 0-39).", + "measure_type": "Incidence", + "unit": "Cases per 1,000,000" }, { - "name": "rate_pneumonitis_due_to_solids_and_liquids", - "short_name": "Aspiration pneumonitis mortality rate", - "description": "Quarterly age-adjusted death rate from pneumonitis due to solids and liquids per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" + "name": "nccr_neoplasms_other_and_nos_lcl", + "short_name": "XII. Other/ Unspecified Neoplasms", + "description": "Lower bound of the 95% confidence interval for the incidence rate of XII. Other/ Unspecified Neoplasms.", + "measure_type": "Incidence", + "unit": "Cases per 1,000,000" }, { - "name": "rate_stroke", - "short_name": "Stroke mortality rate", - "description": "Quarterly age-adjusted death rate from stroke per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" + "name": "nccr_neoplasms_other_and_nos_ucl", + "short_name": "XII. Other/ Unspecified Neoplasms", + "description": "Upper bound of the 95% confidence interval for the incidence rate of XII. Other/ Unspecified Neoplasms.", + "measure_type": "Incidence", + "unit": "Cases per 1,000,000" }, { - "name": "rate_suicide", - "short_name": "Suicide mortality rate", - "description": "Quarterly age-adjusted death rate from suicide per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" + "name": "nccr_neoplasms_other_and_nos_suppressed", + "short_name": "XII. Other/ Unspecified Neoplasms", + "description": "Indicates whether the XII. Other/ Unspecified Neoplasms incidence rate was suppressed (reported as 0 with no confidence interval).", + "measure_type": "Incidence", + "unit": "Cases per 1,000,000" }, { - "name": "rate_unintentional_injuries", - "short_name": "Unintentional injury mortality rate", - "description": "Quarterly age-adjusted death rate from unintentional injuries per 100,000 population.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" + "name": "nccr_neoplasms_other_and_nos_not_collected", + "short_name": "XII. Other/ Unspecified Neoplasms", + "description": "Indicates whether the XII. Other/ Unspecified Neoplasms incidence rate was absent from the API response.", + "measure_type": "Incidence", + "unit": "Cases per 1,000,000" } ] - }, + } + ] + }, + "nchs_mortality": { + "name": "nchs_mortality", + "display_name": "NCHS Mortality", + "description": "The National Center for Health Statistics (NCHS) houses the the Vital Statistics Rapid Release (VSRR) program. The program reports monthly deaths from drug overdose at the state level and quarterly deaths from drug overdose at the county level, as well as quarterly age-adjusted mortality rates for 21 selected causes of death at the state level. Rates are expressed as per 100,000 people. Counts of 19 deaths are suppressed to protect privacy and imputed as 5; the suppressed_flag column identifies these records. Data from the VSSR program and are provisional, meaning they are subject to revision as more death certificates are received and processed. New York City and New York State are combined.", + "standard_files": [ { "filename": "data.csv.gz", "columns": [ @@ -21242,16 +21925,9 @@ "unit": "Binary indicator" } ] - } - ] - }, - "neiss": { - "name": "neiss", - "display_name": "Neiss", - "description": "NEISS is a national probability sample of hospital emergency departments (~100 of the ~5,000+ U.S. hospitals with 24-hour EDs) operated by the U.S. Consumer Product Safety Commission. Each sampled record describes an injury treated in the ED, including patient age, sex, race, Hispanic ethnicity (added 2019), diagnosis, body part, disposition, up to three associated consumer products, and a statistical weight (plus sampling stratum and PSU). Sample weights scale records to national estimates; raw record counts are not nationally representative. This dataset covers treatment years from 2019 through the latest year CPSC has posted (auto-detected at ingest time), aggregated to national (geography='00') annual counts, in wide format: one neiss_n_ (raw sampled count) and one neiss_wt_ (weighted national estimate) column per primary-diagnosis or primary-product-group category. Product groups are reconstructed from NEISS product-code bands and are approximate, not an official CPSC taxonomy. Companion _rate files (data_*_rate.csv.gz) give injury rates per 100,000 population stratified by age and sex only, using the weighted estimate as numerator and a constant national age x sex population (mean of U.S. Census Vintage 2023 estimates, 2020-2023) as denominator.", - "standard_files": [ + }, { - "filename": "data_agegroup_diagnosis_rate.csv.gz", + "filename": "data_county.csv.gz", "columns": [ { "name": "geography", @@ -21268,231 +21944,201 @@ "unit": "date" }, { - "name": "age", - "short_name": "Age", - "description": "Patient age: age in completed months (00-23 months) in the infant files; a standard age band in the age-group files.", - "measure_type": "categorical", - "unit": "category" - }, - { - "name": "sex", - "short_name": "Sex", - "description": "Patient sex (Male, Female, Unknown).", - "measure_type": "categorical", - "unit": "category" - }, - { - "name": "neiss_rate_amputation", - "short_name": "Amputation injury rate", - "description": "Annual ED injury visits with a primary diagnosis of amputation per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_anoxia", - "short_name": "Anoxia injury rate", - "description": "Annual ED injury visits with a primary diagnosis of anoxia per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_aspirated_object", - "short_name": "Aspirated object injury rate", - "description": "Annual ED injury visits with a primary diagnosis of aspirated object per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_avulsion", - "short_name": "Avulsion injury rate", - "description": "Annual ED injury visits with a primary diagnosis of avulsion per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_burns_chemical", - "short_name": "Chemical burns injury rate", - "description": "Annual ED injury visits with a primary diagnosis of chemical burns per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "name": "n_deaths_overdose", + "short_name": "Drug overdose deaths", + "description": "Provisional count of drug overdose deaths. State-level data are 12-month rolling totals; county-level data are monthly.", + "measure_type": "Count", + "unit": "Deaths" }, { - "name": "neiss_rate_burns_elec", - "short_name": "Electrical burns injury rate", - "description": "Annual ED injury visits with a primary diagnosis of electrical burns per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "name": "suppressed", + "short_name": "Drug overdose suppression flag", + "description": "Indicates whether the county drug overdose death count was suppressed by NCHS. Due to privacy protections, counts fewer than 10 are suppressed and imputed to be 5.", + "measure_type": "Binary", + "unit": "Binary indicator" }, { - "name": "neiss_rate_burns_radiation", - "short_name": "Radiation burns injury rate", - "description": "Annual ED injury visits with a primary diagnosis of radiation burns per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, + "name": "pct_pending_invest", + "short_name": "Percent pending investigation", + "description": "Percentage of death records still pending investigation for the reporting period.", + "measure_type": "Percent", + "unit": "Percent" + } + ] + }, + { + "filename": "data_state_21_causes.csv.gz", + "columns": [ { - "name": "neiss_rate_burns_scald", - "short_name": "Scald burns injury rate", - "description": "Annual ED injury visits with a primary diagnosis of scald burns per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "name": "geography", + "short_name": "Geography", + "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", + "measure_type": "identifier", + "unit": "FIPS code" }, { - "name": "neiss_rate_burns_thermal", - "short_name": "Thermal burns injury rate", - "description": "Annual ED injury visits with a primary diagnosis of thermal burns per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date" }, { - "name": "neiss_rate_concussion", - "short_name": "Concussion injury rate", - "description": "Annual ED injury visits with a primary diagnosis of concussion per 100,000 U.S. population, by age and sex.", + "name": "rate_all_causes", + "short_name": "All-cause mortality rate", + "description": "Quarterly age-adjusted death rate from all causes per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_contusion_or_abrasion", - "short_name": "Contusion or abrasion injury rate", - "description": "Annual ED injury visits with a primary diagnosis of contusion or abrasion per 100,000 U.S. population, by age and sex.", + "name": "rate_alzheimer_disease", + "short_name": "Alzheimer's mortality rate", + "description": "Quarterly age-adjusted death rate from Alzheimer's disease per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_crushing", - "short_name": "Crushing injury injury rate", - "description": "Annual ED injury visits with a primary diagnosis of crushing injury per 100,000 U.S. population, by age and sex.", + "name": "rate_covid_19", + "short_name": "COVID-19 mortality rate", + "description": "Quarterly age-adjusted death rate from COVID-19 per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_dental_injury", - "short_name": "Dental injury injury rate", - "description": "Annual ED injury visits with a primary diagnosis of dental injury per 100,000 U.S. population, by age and sex.", + "name": "rate_cancer", + "short_name": "Cancer mortality rate", + "description": "Quarterly age-adjusted death rate from cancer per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_dermat_or_conj", - "short_name": "Dermatitis or conjunctivitis injury rate", - "description": "Annual ED injury visits with a primary diagnosis of dermatitis or conjunctivitis per 100,000 U.S. population, by age and sex.", + "name": "rate_chronic_liver_disease_and_cirrhosis", + "short_name": "Liver disease mortality rate", + "description": "Quarterly age-adjusted death rate from chronic liver disease and cirrhosis per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_dislocation", - "short_name": "Dislocation injury rate", - "description": "Annual ED injury visits with a primary diagnosis of dislocation per 100,000 U.S. population, by age and sex.", + "name": "rate_chronic_lower_respiratory_diseases", + "short_name": "CLRD mortality rate", + "description": "Quarterly age-adjusted death rate from chronic lower respiratory diseases per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_electric_shock", - "short_name": "Electric shock injury rate", - "description": "Annual ED injury visits with a primary diagnosis of electric shock per 100,000 U.S. population, by age and sex.", + "name": "rate_diabetes", + "short_name": "Diabetes mortality rate", + "description": "Quarterly age-adjusted death rate from diabetes per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_foreign_body", - "short_name": "Foreign body injury rate", - "description": "Annual ED injury visits with a primary diagnosis of foreign body per 100,000 U.S. population, by age and sex.", + "name": "rate_drug_overdose", + "short_name": "Drug overdose mortality rate", + "description": "Quarterly age-adjusted death rate from drug overdose per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_fracture", - "short_name": "Fracture injury rate", - "description": "Annual ED injury visits with a primary diagnosis of fracture per 100,000 U.S. population, by age and sex.", + "name": "rate_falls_ages_65_and_over", + "short_name": "Falls mortality rate (65+)", + "description": "Quarterly age-adjusted death rate from falls among adults 65 and over per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_hematoma", - "short_name": "Hematoma injury rate", - "description": "Annual ED injury visits with a primary diagnosis of hematoma per 100,000 U.S. population, by age and sex.", + "name": "rate_firearm_related_injury", + "short_name": "Firearm injury mortality rate", + "description": "Quarterly age-adjusted death rate from firearm-related injuries per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_hemorrhage", - "short_name": "Hemorrhage injury rate", - "description": "Annual ED injury visits with a primary diagnosis of hemorrhage per 100,000 U.S. population, by age and sex.", + "name": "rate_heart_disease", + "short_name": "Heart disease mortality rate", + "description": "Quarterly age-adjusted death rate from heart disease per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_ingested_object", - "short_name": "Ingested object injury rate", - "description": "Annual ED injury visits with a primary diagnosis of ingested object per 100,000 U.S. population, by age and sex.", + "name": "rate_hiv_disease", + "short_name": "HIV mortality rate", + "description": "Quarterly age-adjusted death rate from HIV disease per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_inter_organ_injury", - "short_name": "Internal organ injury injury rate", - "description": "Annual ED injury visits with a primary diagnosis of internal organ injury per 100,000 U.S. population, by age and sex.", + "name": "rate_homicide", + "short_name": "Homicide mortality rate", + "description": "Quarterly age-adjusted death rate from homicide per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_laceration", - "short_name": "Laceration injury rate", - "description": "Annual ED injury visits with a primary diagnosis of laceration per 100,000 U.S. population, by age and sex.", + "name": "rate_hypertension", + "short_name": "Hypertension mortality rate", + "description": "Quarterly age-adjusted death rate from hypertension per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_nerve_damage", - "short_name": "Nerve damage injury rate", - "description": "Annual ED injury visits with a primary diagnosis of nerve damage per 100,000 U.S. population, by age and sex.", + "name": "rate_influenza_and_pneumonia", + "short_name": "Flu & pneumonia mortality rate", + "description": "Quarterly age-adjusted death rate from influenza and pneumonia per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_other_or_not_stated", - "short_name": "Other or not stated injury rate", - "description": "Annual ED injury visits with a primary diagnosis of other or not stated per 100,000 U.S. population, by age and sex.", + "name": "rate_kidney_disease", + "short_name": "Kidney disease mortality rate", + "description": "Quarterly age-adjusted death rate from kidney disease per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_poisoning", - "short_name": "Poisoning injury rate", - "description": "Annual ED injury visits with a primary diagnosis of poisoning per 100,000 U.S. population, by age and sex.", + "name": "rate_parkinson_disease", + "short_name": "Parkinson's mortality rate", + "description": "Quarterly age-adjusted death rate from Parkinson's disease per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_puncture", - "short_name": "Puncture injury rate", - "description": "Annual ED injury visits with a primary diagnosis of puncture per 100,000 U.S. population, by age and sex.", + "name": "rate_pneumonitis_due_to_solids_and_liquids", + "short_name": "Aspiration pneumonitis mortality rate", + "description": "Quarterly age-adjusted death rate from pneumonitis due to solids and liquids per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_strain_sprain", - "short_name": "Strain or sprain injury rate", - "description": "Annual ED injury visits with a primary diagnosis of strain or sprain per 100,000 U.S. population, by age and sex.", + "name": "rate_stroke", + "short_name": "Stroke mortality rate", + "description": "Quarterly age-adjusted death rate from stroke per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_submersion", - "short_name": "Submersion injury rate", - "description": "Annual ED injury visits with a primary diagnosis of submersion per 100,000 U.S. population, by age and sex.", + "name": "rate_suicide", + "short_name": "Suicide mortality rate", + "description": "Quarterly age-adjusted death rate from suicide per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" }, { - "name": "neiss_rate_burns_not_spec", - "short_name": "Burns (unspecified) injury rate", - "description": "Annual ED injury visits with a primary diagnosis of burns (unspecified) per 100,000 U.S. population, by age and sex.", + "name": "rate_unintentional_injuries", + "short_name": "Unintentional injury mortality rate", + "description": "Quarterly age-adjusted death rate from unintentional injuries per 100,000 population.", "measure_type": "Rate", - "unit": "Injuries per 100,000 population" + "unit": "Deaths per 100,000" } ] - }, + } + ] + }, + "neiss": { + "name": "neiss", + "display_name": "Neiss", + "description": "NEISS is a national probability sample of hospital emergency departments (~100 of the ~5,000+ U.S. hospitals with 24-hour EDs) operated by the U.S. Consumer Product Safety Commission. Each sampled record describes an injury treated in the ED, including patient age, sex, race, Hispanic ethnicity (added 2019), diagnosis, body part, disposition, up to three associated consumer products, and a statistical weight (plus sampling stratum and PSU). Sample weights scale records to national estimates; raw record counts are not nationally representative. This dataset covers treatment years from 2019 through the latest year CPSC has posted (auto-detected at ingest time), aggregated to national (geography='00') annual counts, in wide format: one neiss_n_ (raw sampled count) and one neiss_wt_ (weighted national estimate) column per primary-diagnosis or primary-product-group category. Product groups are reconstructed from NEISS product-code bands and are approximate, not an official CPSC taxonomy. Companion _rate files (data_*_rate.csv.gz) give injury rates per 100,000 population stratified by age and sex only, using the weighted estimate as numerator and a constant national age x sex population (mean of U.S. Census Vintage 2023 estimates, 2020-2023) as denominator.", + "standard_files": [ { "filename": "data_agegroup_diagnosis.csv.gz", "columns": [ @@ -21961,7 +22607,7 @@ ] }, { - "filename": "data_agegroup_product_rate.csv.gz", + "filename": "data_agegroup_diagnosis_rate.csv.gz", "columns": [ { "name": "geography", @@ -21971,135 +22617,233 @@ "unit": "FIPS code" }, { - "name": "time", - "short_name": "Time", - "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", - "measure_type": "date", - "unit": "date" + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date" + }, + { + "name": "age", + "short_name": "Age", + "description": "Patient age: age in completed months (00-23 months) in the infant files; a standard age band in the age-group files.", + "measure_type": "categorical", + "unit": "category" + }, + { + "name": "sex", + "short_name": "Sex", + "description": "Patient sex (Male, Female, Unknown).", + "measure_type": "categorical", + "unit": "category" + }, + { + "name": "neiss_rate_amputation", + "short_name": "Amputation injury rate", + "description": "Annual ED injury visits with a primary diagnosis of amputation per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_anoxia", + "short_name": "Anoxia injury rate", + "description": "Annual ED injury visits with a primary diagnosis of anoxia per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_aspirated_object", + "short_name": "Aspirated object injury rate", + "description": "Annual ED injury visits with a primary diagnosis of aspirated object per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_avulsion", + "short_name": "Avulsion injury rate", + "description": "Annual ED injury visits with a primary diagnosis of avulsion per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_burns_chemical", + "short_name": "Chemical burns injury rate", + "description": "Annual ED injury visits with a primary diagnosis of chemical burns per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_burns_elec", + "short_name": "Electrical burns injury rate", + "description": "Annual ED injury visits with a primary diagnosis of electrical burns per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_burns_radiation", + "short_name": "Radiation burns injury rate", + "description": "Annual ED injury visits with a primary diagnosis of radiation burns per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_burns_scald", + "short_name": "Scald burns injury rate", + "description": "Annual ED injury visits with a primary diagnosis of scald burns per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_burns_thermal", + "short_name": "Thermal burns injury rate", + "description": "Annual ED injury visits with a primary diagnosis of thermal burns per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_concussion", + "short_name": "Concussion injury rate", + "description": "Annual ED injury visits with a primary diagnosis of concussion per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_contusion_or_abrasion", + "short_name": "Contusion or abrasion injury rate", + "description": "Annual ED injury visits with a primary diagnosis of contusion or abrasion per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_crushing", + "short_name": "Crushing injury injury rate", + "description": "Annual ED injury visits with a primary diagnosis of crushing injury per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" }, { - "name": "age", - "short_name": "Age", - "description": "Patient age: age in completed months (00-23 months) in the infant files; a standard age band in the age-group files.", - "measure_type": "categorical", - "unit": "category" + "name": "neiss_rate_dental_injury", + "short_name": "Dental injury injury rate", + "description": "Annual ED injury visits with a primary diagnosis of dental injury per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" }, { - "name": "sex", - "short_name": "Sex", - "description": "Patient sex (Male, Female, Unknown).", - "measure_type": "categorical", - "unit": "category" + "name": "neiss_rate_dermat_or_conj", + "short_name": "Dermatitis or conjunctivitis injury rate", + "description": "Annual ED injury visits with a primary diagnosis of dermatitis or conjunctivitis per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_chemicals", - "short_name": "Chemicals injury rate", - "description": "Annual ED injury visits whose primary product was chemicals per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_dislocation", + "short_name": "Dislocation injury rate", + "description": "Annual ED injury visits with a primary diagnosis of dislocation per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_child_nursery_equipment", - "short_name": "Child nursery equipment injury rate", - "description": "Annual ED injury visits whose primary product was child nursery equipment per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_electric_shock", + "short_name": "Electric shock injury rate", + "description": "Annual ED injury visits with a primary diagnosis of electric shock per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_general_household_appliances", - "short_name": "General household appliances injury rate", - "description": "Annual ED injury visits whose primary product was general household appliances per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_foreign_body", + "short_name": "Foreign body injury rate", + "description": "Annual ED injury visits with a primary diagnosis of foreign body per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_heating_cooling_ventilation", - "short_name": "Heating, cooling & ventilation injury rate", - "description": "Annual ED injury visits whose primary product was heating, cooling & ventilation per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_fracture", + "short_name": "Fracture injury rate", + "description": "Annual ED injury visits with a primary diagnosis of fracture per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_home_communication_entertainment_hobby", - "short_name": "Home communication, entertainment & hobby injury rate", - "description": "Annual ED injury visits whose primary product was home communication, entertainment & hobby per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_hematoma", + "short_name": "Hematoma injury rate", + "description": "Annual ED injury visits with a primary diagnosis of hematoma per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_home_furnishings_fixtures", - "short_name": "Home furnishings & fixtures injury rate", - "description": "Annual ED injury visits whose primary product was home furnishings & fixtures per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_hemorrhage", + "short_name": "Hemorrhage injury rate", + "description": "Annual ED injury visits with a primary diagnosis of hemorrhage per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_home_structures_construction_materials", - "short_name": "Home structures & construction materials injury rate", - "description": "Annual ED injury visits whose primary product was home structures & construction materials per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_ingested_object", + "short_name": "Ingested object injury rate", + "description": "Annual ED injury visits with a primary diagnosis of ingested object per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_home_workshop_equipment_tools", - "short_name": "Home workshop equipment & tools injury rate", - "description": "Annual ED injury visits whose primary product was home workshop equipment & tools per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_inter_organ_injury", + "short_name": "Internal organ injury injury rate", + "description": "Annual ED injury visits with a primary diagnosis of internal organ injury per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_housewares", - "short_name": "Housewares injury rate", - "description": "Annual ED injury visits whose primary product was housewares per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_laceration", + "short_name": "Laceration injury rate", + "description": "Annual ED injury visits with a primary diagnosis of laceration per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_kitchen_appliances", - "short_name": "Kitchen appliances injury rate", - "description": "Annual ED injury visits whose primary product was kitchen appliances per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_nerve_damage", + "short_name": "Nerve damage injury rate", + "description": "Annual ED injury visits with a primary diagnosis of nerve damage per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_other_unspecified", - "short_name": "Other/unspecified product injury rate", - "description": "Annual ED injury visits whose primary product was other/unspecified product per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_other_or_not_stated", + "short_name": "Other or not stated injury rate", + "description": "Annual ED injury visits with a primary diagnosis of other or not stated per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_packaging_containers", - "short_name": "Packaging & containers injury rate", - "description": "Annual ED injury visits whose primary product was packaging & containers per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_poisoning", + "short_name": "Poisoning injury rate", + "description": "Annual ED injury visits with a primary diagnosis of poisoning per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_personal_use_drugs_misc", - "short_name": "Personal use, drugs & misc. injury rate", - "description": "Annual ED injury visits whose primary product was personal use, drugs & misc. per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_puncture", + "short_name": "Puncture injury rate", + "description": "Annual ED injury visits with a primary diagnosis of puncture per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_sports_recreation_activities", - "short_name": "Sports & recreation activities injury rate", - "description": "Annual ED injury visits whose primary product was sports & recreation activities per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_strain_sprain", + "short_name": "Strain or sprain injury rate", + "description": "Annual ED injury visits with a primary diagnosis of strain or sprain per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_sports_recreation_equipment_toys", - "short_name": "Sports/recreation equipment & toys injury rate", - "description": "Annual ED injury visits whose primary product was sports/recreation equipment & toys per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_submersion", + "short_name": "Submersion injury rate", + "description": "Annual ED injury visits with a primary diagnosis of submersion per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_yard_garden_equipment", - "short_name": "Yard & garden equipment injury rate", - "description": "Annual ED injury visits whose primary product was yard & garden equipment per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_burns_not_spec", + "short_name": "Burns (unspecified) injury rate", + "description": "Annual ED injury visits with a primary diagnosis of burns (unspecified) per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" } @@ -22377,7 +23121,7 @@ ] }, { - "filename": "data_infant_diagnosis_rate.csv.gz", + "filename": "data_agegroup_product_rate.csv.gz", "columns": [ { "name": "geography", @@ -22408,212 +23152,114 @@ "unit": "category" }, { - "name": "neiss_rate_fracture", - "short_name": "Fracture injury rate", - "description": "Annual ED injury visits with a primary diagnosis of fracture per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_inter_organ_injury", - "short_name": "Internal organ injury injury rate", - "description": "Annual ED injury visits with a primary diagnosis of internal organ injury per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_laceration", - "short_name": "Laceration injury rate", - "description": "Annual ED injury visits with a primary diagnosis of laceration per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_other_or_not_stated", - "short_name": "Other or not stated injury rate", - "description": "Annual ED injury visits with a primary diagnosis of other or not stated per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_strain_sprain", - "short_name": "Strain or sprain injury rate", - "description": "Annual ED injury visits with a primary diagnosis of strain or sprain per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_anoxia", - "short_name": "Anoxia injury rate", - "description": "Annual ED injury visits with a primary diagnosis of anoxia per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_burns_thermal", - "short_name": "Thermal burns injury rate", - "description": "Annual ED injury visits with a primary diagnosis of thermal burns per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_contusion_or_abrasion", - "short_name": "Contusion or abrasion injury rate", - "description": "Annual ED injury visits with a primary diagnosis of contusion or abrasion per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_poisoning", - "short_name": "Poisoning injury rate", - "description": "Annual ED injury visits with a primary diagnosis of poisoning per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_aspirated_object", - "short_name": "Aspirated object injury rate", - "description": "Annual ED injury visits with a primary diagnosis of aspirated object per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_burns_chemical", - "short_name": "Chemical burns injury rate", - "description": "Annual ED injury visits with a primary diagnosis of chemical burns per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_burns_scald", - "short_name": "Scald burns injury rate", - "description": "Annual ED injury visits with a primary diagnosis of scald burns per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_concussion", - "short_name": "Concussion injury rate", - "description": "Annual ED injury visits with a primary diagnosis of concussion per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_dermat_or_conj", - "short_name": "Dermatitis or conjunctivitis injury rate", - "description": "Annual ED injury visits with a primary diagnosis of dermatitis or conjunctivitis per 100,000 U.S. population, by age and sex.", - "measure_type": "Rate", - "unit": "Injuries per 100,000 population" - }, - { - "name": "neiss_rate_foreign_body", - "short_name": "Foreign body injury rate", - "description": "Annual ED injury visits with a primary diagnosis of foreign body per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_chemicals", + "short_name": "Chemicals injury rate", + "description": "Annual ED injury visits whose primary product was chemicals per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_hematoma", - "short_name": "Hematoma injury rate", - "description": "Annual ED injury visits with a primary diagnosis of hematoma per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_child_nursery_equipment", + "short_name": "Child nursery equipment injury rate", + "description": "Annual ED injury visits whose primary product was child nursery equipment per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_hemorrhage", - "short_name": "Hemorrhage injury rate", - "description": "Annual ED injury visits with a primary diagnosis of hemorrhage per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_general_household_appliances", + "short_name": "General household appliances injury rate", + "description": "Annual ED injury visits whose primary product was general household appliances per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_ingested_object", - "short_name": "Ingested object injury rate", - "description": "Annual ED injury visits with a primary diagnosis of ingested object per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_heating_cooling_ventilation", + "short_name": "Heating, cooling & ventilation injury rate", + "description": "Annual ED injury visits whose primary product was heating, cooling & ventilation per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_crushing", - "short_name": "Crushing injury injury rate", - "description": "Annual ED injury visits with a primary diagnosis of crushing injury per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_home_communication_entertainment_hobby", + "short_name": "Home communication, entertainment & hobby injury rate", + "description": "Annual ED injury visits whose primary product was home communication, entertainment & hobby per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_nerve_damage", - "short_name": "Nerve damage injury rate", - "description": "Annual ED injury visits with a primary diagnosis of nerve damage per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_home_furnishings_fixtures", + "short_name": "Home furnishings & fixtures injury rate", + "description": "Annual ED injury visits whose primary product was home furnishings & fixtures per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_submersion", - "short_name": "Submersion injury rate", - "description": "Annual ED injury visits with a primary diagnosis of submersion per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_home_structures_construction_materials", + "short_name": "Home structures & construction materials injury rate", + "description": "Annual ED injury visits whose primary product was home structures & construction materials per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_dislocation", - "short_name": "Dislocation injury rate", - "description": "Annual ED injury visits with a primary diagnosis of dislocation per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_home_workshop_equipment_tools", + "short_name": "Home workshop equipment & tools injury rate", + "description": "Annual ED injury visits whose primary product was home workshop equipment & tools per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_avulsion", - "short_name": "Avulsion injury rate", - "description": "Annual ED injury visits with a primary diagnosis of avulsion per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_housewares", + "short_name": "Housewares injury rate", + "description": "Annual ED injury visits whose primary product was housewares per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_dental_injury", - "short_name": "Dental injury injury rate", - "description": "Annual ED injury visits with a primary diagnosis of dental injury per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_kitchen_appliances", + "short_name": "Kitchen appliances injury rate", + "description": "Annual ED injury visits whose primary product was kitchen appliances per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_puncture", - "short_name": "Puncture injury rate", - "description": "Annual ED injury visits with a primary diagnosis of puncture per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_other_unspecified", + "short_name": "Other/unspecified product injury rate", + "description": "Annual ED injury visits whose primary product was other/unspecified product per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_amputation", - "short_name": "Amputation injury rate", - "description": "Annual ED injury visits with a primary diagnosis of amputation per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_packaging_containers", + "short_name": "Packaging & containers injury rate", + "description": "Annual ED injury visits whose primary product was packaging & containers per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_burns_not_spec", - "short_name": "Burns (unspecified) injury rate", - "description": "Annual ED injury visits with a primary diagnosis of burns (unspecified) per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_personal_use_drugs_misc", + "short_name": "Personal use, drugs & misc. injury rate", + "description": "Annual ED injury visits whose primary product was personal use, drugs & misc. per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_electric_shock", - "short_name": "Electric shock injury rate", - "description": "Annual ED injury visits with a primary diagnosis of electric shock per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_sports_recreation_activities", + "short_name": "Sports & recreation activities injury rate", + "description": "Annual ED injury visits whose primary product was sports & recreation activities per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_burns_elec", - "short_name": "Electrical burns injury rate", - "description": "Annual ED injury visits with a primary diagnosis of electrical burns per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_sports_recreation_equipment_toys", + "short_name": "Sports/recreation equipment & toys injury rate", + "description": "Annual ED injury visits whose primary product was sports/recreation equipment & toys per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_burns_radiation", - "short_name": "Radiation burns injury rate", - "description": "Annual ED injury visits with a primary diagnosis of radiation burns per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_yard_garden_equipment", + "short_name": "Yard & garden equipment injury rate", + "description": "Annual ED injury visits whose primary product was yard & garden equipment per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" } @@ -23087,7 +23733,7 @@ ] }, { - "filename": "data_infant_product_rate.csv.gz", + "filename": "data_infant_diagnosis_rate.csv.gz", "columns": [ { "name": "geography", @@ -23118,114 +23764,212 @@ "unit": "category" }, { - "name": "neiss_rate_home_furnishings_fixtures", - "short_name": "Home furnishings & fixtures injury rate", - "description": "Annual ED injury visits whose primary product was home furnishings & fixtures per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_fracture", + "short_name": "Fracture injury rate", + "description": "Annual ED injury visits with a primary diagnosis of fracture per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_personal_use_drugs_misc", - "short_name": "Personal use, drugs & misc. injury rate", - "description": "Annual ED injury visits whose primary product was personal use, drugs & misc. per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_inter_organ_injury", + "short_name": "Internal organ injury injury rate", + "description": "Annual ED injury visits with a primary diagnosis of internal organ injury per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_sports_recreation_activities", - "short_name": "Sports & recreation activities injury rate", - "description": "Annual ED injury visits whose primary product was sports & recreation activities per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_laceration", + "short_name": "Laceration injury rate", + "description": "Annual ED injury visits with a primary diagnosis of laceration per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_child_nursery_equipment", - "short_name": "Child nursery equipment injury rate", - "description": "Annual ED injury visits whose primary product was child nursery equipment per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_other_or_not_stated", + "short_name": "Other or not stated injury rate", + "description": "Annual ED injury visits with a primary diagnosis of other or not stated per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_housewares", - "short_name": "Housewares injury rate", - "description": "Annual ED injury visits whose primary product was housewares per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_strain_sprain", + "short_name": "Strain or sprain injury rate", + "description": "Annual ED injury visits with a primary diagnosis of strain or sprain per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_sports_recreation_equipment_toys", - "short_name": "Sports/recreation equipment & toys injury rate", - "description": "Annual ED injury visits whose primary product was sports/recreation equipment & toys per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_anoxia", + "short_name": "Anoxia injury rate", + "description": "Annual ED injury visits with a primary diagnosis of anoxia per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_chemicals", - "short_name": "Chemicals injury rate", - "description": "Annual ED injury visits whose primary product was chemicals per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_burns_thermal", + "short_name": "Thermal burns injury rate", + "description": "Annual ED injury visits with a primary diagnosis of thermal burns per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_home_communication_entertainment_hobby", - "short_name": "Home communication, entertainment & hobby injury rate", - "description": "Annual ED injury visits whose primary product was home communication, entertainment & hobby per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_contusion_or_abrasion", + "short_name": "Contusion or abrasion injury rate", + "description": "Annual ED injury visits with a primary diagnosis of contusion or abrasion per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_home_structures_construction_materials", - "short_name": "Home structures & construction materials injury rate", - "description": "Annual ED injury visits whose primary product was home structures & construction materials per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_poisoning", + "short_name": "Poisoning injury rate", + "description": "Annual ED injury visits with a primary diagnosis of poisoning per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_home_workshop_equipment_tools", - "short_name": "Home workshop equipment & tools injury rate", - "description": "Annual ED injury visits whose primary product was home workshop equipment & tools per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_aspirated_object", + "short_name": "Aspirated object injury rate", + "description": "Annual ED injury visits with a primary diagnosis of aspirated object per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_kitchen_appliances", - "short_name": "Kitchen appliances injury rate", - "description": "Annual ED injury visits whose primary product was kitchen appliances per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_burns_chemical", + "short_name": "Chemical burns injury rate", + "description": "Annual ED injury visits with a primary diagnosis of chemical burns per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_packaging_containers", - "short_name": "Packaging & containers injury rate", - "description": "Annual ED injury visits whose primary product was packaging & containers per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_burns_scald", + "short_name": "Scald burns injury rate", + "description": "Annual ED injury visits with a primary diagnosis of scald burns per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_heating_cooling_ventilation", - "short_name": "Heating, cooling & ventilation injury rate", - "description": "Annual ED injury visits whose primary product was heating, cooling & ventilation per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_concussion", + "short_name": "Concussion injury rate", + "description": "Annual ED injury visits with a primary diagnosis of concussion per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_other_unspecified", - "short_name": "Other/unspecified product injury rate", - "description": "Annual ED injury visits whose primary product was other/unspecified product per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_dermat_or_conj", + "short_name": "Dermatitis or conjunctivitis injury rate", + "description": "Annual ED injury visits with a primary diagnosis of dermatitis or conjunctivitis per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_foreign_body", + "short_name": "Foreign body injury rate", + "description": "Annual ED injury visits with a primary diagnosis of foreign body per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_hematoma", + "short_name": "Hematoma injury rate", + "description": "Annual ED injury visits with a primary diagnosis of hematoma per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_hemorrhage", + "short_name": "Hemorrhage injury rate", + "description": "Annual ED injury visits with a primary diagnosis of hemorrhage per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_ingested_object", + "short_name": "Ingested object injury rate", + "description": "Annual ED injury visits with a primary diagnosis of ingested object per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_crushing", + "short_name": "Crushing injury injury rate", + "description": "Annual ED injury visits with a primary diagnosis of crushing injury per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_nerve_damage", + "short_name": "Nerve damage injury rate", + "description": "Annual ED injury visits with a primary diagnosis of nerve damage per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_submersion", + "short_name": "Submersion injury rate", + "description": "Annual ED injury visits with a primary diagnosis of submersion per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_dislocation", + "short_name": "Dislocation injury rate", + "description": "Annual ED injury visits with a primary diagnosis of dislocation per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_avulsion", + "short_name": "Avulsion injury rate", + "description": "Annual ED injury visits with a primary diagnosis of avulsion per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_dental_injury", + "short_name": "Dental injury injury rate", + "description": "Annual ED injury visits with a primary diagnosis of dental injury per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_puncture", + "short_name": "Puncture injury rate", + "description": "Annual ED injury visits with a primary diagnosis of puncture per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_amputation", + "short_name": "Amputation injury rate", + "description": "Annual ED injury visits with a primary diagnosis of amputation per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_burns_not_spec", + "short_name": "Burns (unspecified) injury rate", + "description": "Annual ED injury visits with a primary diagnosis of burns (unspecified) per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_electric_shock", + "short_name": "Electric shock injury rate", + "description": "Annual ED injury visits with a primary diagnosis of electric shock per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_yard_garden_equipment", - "short_name": "Yard & garden equipment injury rate", - "description": "Annual ED injury visits whose primary product was yard & garden equipment per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_burns_elec", + "short_name": "Electrical burns injury rate", + "description": "Annual ED injury visits with a primary diagnosis of electrical burns per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" }, { - "name": "neiss_rate_general_household_appliances", - "short_name": "General household appliances injury rate", - "description": "Annual ED injury visits whose primary product was general household appliances per 100,000 U.S. population, by age and sex.", + "name": "neiss_rate_burns_radiation", + "short_name": "Radiation burns injury rate", + "description": "Annual ED injury visits with a primary diagnosis of radiation burns per 100,000 U.S. population, by age and sex.", "measure_type": "Rate", "unit": "Injuries per 100,000 population" } @@ -23501,6 +24245,151 @@ "unit": "visits" } ] + }, + { + "filename": "data_infant_product_rate.csv.gz", + "columns": [ + { + "name": "geography", + "short_name": "Geography", + "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", + "measure_type": "identifier", + "unit": "FIPS code" + }, + { + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date" + }, + { + "name": "age", + "short_name": "Age", + "description": "Patient age: age in completed months (00-23 months) in the infant files; a standard age band in the age-group files.", + "measure_type": "categorical", + "unit": "category" + }, + { + "name": "sex", + "short_name": "Sex", + "description": "Patient sex (Male, Female, Unknown).", + "measure_type": "categorical", + "unit": "category" + }, + { + "name": "neiss_rate_home_furnishings_fixtures", + "short_name": "Home furnishings & fixtures injury rate", + "description": "Annual ED injury visits whose primary product was home furnishings & fixtures per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_personal_use_drugs_misc", + "short_name": "Personal use, drugs & misc. injury rate", + "description": "Annual ED injury visits whose primary product was personal use, drugs & misc. per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_sports_recreation_activities", + "short_name": "Sports & recreation activities injury rate", + "description": "Annual ED injury visits whose primary product was sports & recreation activities per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_child_nursery_equipment", + "short_name": "Child nursery equipment injury rate", + "description": "Annual ED injury visits whose primary product was child nursery equipment per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_housewares", + "short_name": "Housewares injury rate", + "description": "Annual ED injury visits whose primary product was housewares per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_sports_recreation_equipment_toys", + "short_name": "Sports/recreation equipment & toys injury rate", + "description": "Annual ED injury visits whose primary product was sports/recreation equipment & toys per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_chemicals", + "short_name": "Chemicals injury rate", + "description": "Annual ED injury visits whose primary product was chemicals per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_home_communication_entertainment_hobby", + "short_name": "Home communication, entertainment & hobby injury rate", + "description": "Annual ED injury visits whose primary product was home communication, entertainment & hobby per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_home_structures_construction_materials", + "short_name": "Home structures & construction materials injury rate", + "description": "Annual ED injury visits whose primary product was home structures & construction materials per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_home_workshop_equipment_tools", + "short_name": "Home workshop equipment & tools injury rate", + "description": "Annual ED injury visits whose primary product was home workshop equipment & tools per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_kitchen_appliances", + "short_name": "Kitchen appliances injury rate", + "description": "Annual ED injury visits whose primary product was kitchen appliances per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_packaging_containers", + "short_name": "Packaging & containers injury rate", + "description": "Annual ED injury visits whose primary product was packaging & containers per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_heating_cooling_ventilation", + "short_name": "Heating, cooling & ventilation injury rate", + "description": "Annual ED injury visits whose primary product was heating, cooling & ventilation per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_other_unspecified", + "short_name": "Other/unspecified product injury rate", + "description": "Annual ED injury visits whose primary product was other/unspecified product per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_yard_garden_equipment", + "short_name": "Yard & garden equipment injury rate", + "description": "Annual ED injury visits whose primary product was yard & garden equipment per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + }, + { + "name": "neiss_rate_general_household_appliances", + "short_name": "General household appliances injury rate", + "description": "Annual ED injury visits whose primary product was general household appliances per 100,000 U.S. population, by age and sex.", + "measure_type": "Rate", + "unit": "Injuries per 100,000 population" + } + ] } ] }, @@ -23509,6 +24398,46 @@ "display_name": "Nhtsa Crash", "description": "FARS is a nationwide census providing NHTSA, Congress, and the American public with yearly data on fatal injuries suffered in motor vehicle traffic crashes. FARS contains data on all crashes in the United States involving a fatality in a motor vehicle traffic crash on a public road. A fatal crash is one in which a motor vehicle is involved and at least one person dies within 30 days of the crash. Data are collected from police crash reports, state vehicle registration files, state driver licensing files, state highway department data, vital statistics, and other sources. FARS has been operational since 1975 and covers all 50 states, the District of Columbia, and Puerto Rico (national files cover the 50 states and DC).", "standard_files": [ + { + "filename": "data.csv.gz", + "columns": [ + { + "name": "geography", + "short_name": "Geography", + "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", + "measure_type": "identifier", + "unit": "FIPS code" + }, + { + "name": "time", + "short_name": "Time", + "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", + "measure_type": "date", + "unit": "date" + }, + { + "name": "nhtsa_fatalities", + "short_name": "Motor vehicle fatalities", + "description": "Annual count of persons killed in motor vehicle traffic crashes.", + "measure_type": "Count", + "unit": "Deaths" + }, + { + "name": "nhtsa_fatal_crashes", + "short_name": "Fatal crashes", + "description": "Annual count of motor vehicle crashes resulting in at least one fatality.", + "measure_type": "Count", + "unit": "Crashes" + }, + { + "name": "nhtsa_fatality_rate", + "short_name": "Fatality rate (per 100k)", + "description": "Annual motor vehicle fatalities per 100,000 residents. Population denominator is 2021 Census.", + "measure_type": "Rate", + "unit": "Deaths per 100,000" + } + ] + }, { "filename": "data_age_sex.csv.gz", "columns": [ @@ -23649,24 +24578,80 @@ "unit": "date" }, { - "name": "person_type", - "short_name": "person_type", - "description": "", - "measure_type": "", - "unit": "" + "name": "person_type", + "short_name": "person_type", + "description": "", + "measure_type": "", + "unit": "" + }, + { + "name": "nhtsa_fatalities", + "short_name": "Motor vehicle fatalities", + "description": "Annual count of persons killed in motor vehicle traffic crashes.", + "measure_type": "Count", + "unit": "Deaths" + } + ] + } + ] + }, + "nis": { + "name": "nis", + "display_name": "NIS", + "description": "The National Immunization Surveys (NIS) are a group of telephone surveys used to monitor vaccination coverage among children 19-35 months, teens 13-17 years, flu vaccinations for children 6 months-17 years, and COVID-19 vaccination for children, teens, and adults. The surveys are sponsored and conducted by the National Center for Immunization and Respiratory Diseases (NCIRD) of the CDC and authorized by the Public Health Service Act. NIS provides population-based, state and local area estimates of vaccination coverage using a standard survey methodology. Surveys collect data through telephone interviews with parents or guardians in all 50 states, the District of Columbia, and some U.S. territories. Cell phone numbers are randomly selected and called to enroll age-eligible children. With parental permission, vaccination providers are contacted to verify immunization records. Children and teens are classified as up to date based on ACIP-recommended vaccine doses.", + "standard_files": [ + { + "filename": "data.csv.gz", + "columns": [ + { + "name": "birth_year", + "short_name": "Birth Year", + "description": "Calendar year the child was born.", + "measure_type": "integer", + "unit": "year" + }, + { + "name": "age", + "short_name": "Age", + "description": "Age group of surveyed children.", + "measure_type": "categorical", + "unit": "" + }, + { + "name": "vaccine", + "short_name": "Vaccine", + "description": "Type of vaccine being measured.", + "measure_type": "categorical", + "unit": "" + }, + { + "name": "vax_uptake_overall", + "short_name": "Overall", + "description": "Percent of survey respondents who received the indicated vaccine", + "measure_type": "percent", + "unit": "percent" + }, + { + "name": "vax_uptake_overall_lcl", + "short_name": "Overall lower 95% CI", + "description": "Percent of survey respondents who received the indicated vaccine", + "measure_type": "percent", + "unit": "percent" + }, + { + "name": "vax_uptake_overall_ucl", + "short_name": "Overall upper 95% CI", + "description": "Percent of survey respondents who received the indicated vaccine", + "measure_type": "percent", + "unit": "percent" }, { - "name": "nhtsa_fatalities", - "short_name": "Motor vehicle fatalities", - "description": "Annual count of persons killed in motor vehicle traffic crashes.", - "measure_type": "Count", - "unit": "Deaths" - } - ] - }, - { - "filename": "data.csv.gz", - "columns": [ + "name": "sample_size_overall", + "short_name": "Overall", + "description": "Number of children surveyed for vaccination coverage estimates in the National Immunization Survey (NIS).", + "measure_type": "percent", + "unit": "percent" + }, { "name": "geography", "short_name": "Geography", @@ -23680,37 +24665,9 @@ "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", "measure_type": "date", "unit": "date" - }, - { - "name": "nhtsa_fatalities", - "short_name": "Motor vehicle fatalities", - "description": "Annual count of persons killed in motor vehicle traffic crashes.", - "measure_type": "Count", - "unit": "Deaths" - }, - { - "name": "nhtsa_fatal_crashes", - "short_name": "Fatal crashes", - "description": "Annual count of motor vehicle crashes resulting in at least one fatality.", - "measure_type": "Count", - "unit": "Crashes" - }, - { - "name": "nhtsa_fatality_rate", - "short_name": "Fatality rate (per 100k)", - "description": "Annual motor vehicle fatalities per 100,000 residents. Population denominator is 2021 Census.", - "measure_type": "Rate", - "unit": "Deaths per 100,000" } ] - } - ] - }, - "nis": { - "name": "nis", - "display_name": "NIS", - "description": "The National Immunization Surveys (NIS) are a group of telephone surveys used to monitor vaccination coverage among children 19-35 months, teens 13-17 years, flu vaccinations for children 6 months-17 years, and COVID-19 vaccination for children, teens, and adults. The surveys are sponsored and conducted by the National Center for Immunization and Respiratory Diseases (NCIRD) of the CDC and authorized by the Public Health Service Act. NIS provides population-based, state and local area estimates of vaccination coverage using a standard survey methodology. Surveys collect data through telephone interviews with parents or guardians in all 50 states, the District of Columbia, and some U.S. territories. Cell phone numbers are randomly selected and called to enroll age-eligible children. With parental permission, vaccination providers are contacted to verify immunization records. Children and teens are classified as up to date based on ACIP-recommended vaccine doses.", - "standard_files": [ + }, { "filename": "data_insurance.csv.gz", "columns": [ @@ -23832,74 +24789,6 @@ "unit": "percent" } ] - }, - { - "filename": "data.csv.gz", - "columns": [ - { - "name": "birth_year", - "short_name": "Birth Year", - "description": "Calendar year the child was born.", - "measure_type": "integer", - "unit": "year" - }, - { - "name": "age", - "short_name": "Age", - "description": "Age group of surveyed children.", - "measure_type": "categorical", - "unit": "" - }, - { - "name": "vaccine", - "short_name": "Vaccine", - "description": "Type of vaccine being measured.", - "measure_type": "categorical", - "unit": "" - }, - { - "name": "vax_uptake_overall", - "short_name": "Overall", - "description": "Percent of survey respondents who received the indicated vaccine", - "measure_type": "percent", - "unit": "percent" - }, - { - "name": "vax_uptake_overall_lcl", - "short_name": "Overall lower 95% CI", - "description": "Percent of survey respondents who received the indicated vaccine", - "measure_type": "percent", - "unit": "percent" - }, - { - "name": "vax_uptake_overall_ucl", - "short_name": "Overall upper 95% CI", - "description": "Percent of survey respondents who received the indicated vaccine", - "measure_type": "percent", - "unit": "percent" - }, - { - "name": "sample_size_overall", - "short_name": "Overall", - "description": "Number of children surveyed for vaccination coverage estimates in the National Immunization Survey (NIS).", - "measure_type": "percent", - "unit": "percent" - }, - { - "name": "geography", - "short_name": "Geography", - "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", - "measure_type": "identifier", - "unit": "FIPS code" - }, - { - "name": "time", - "short_name": "Time", - "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", - "measure_type": "date", - "unit": "date" - } - ] } ] }, @@ -24772,7 +25661,7 @@ "noaa_heat_risk": { "name": "noaa_heat_risk", "display_name": "Noaa Heat Risk", - "description": "The NOAA Weather Prediction Center HeatRisk product provides a daily, gridded (2.5 km) assessment of heat risk across the contiguous United States for the current day and 7-day forecast period. Risk is classified on a 0–4 scale based on the combination of heat intensity and duration relative to local historical thresholds, with consideration for overnight low temperatures and heat index. The archive provides daily GeoTIFF rasters back to August 1, 2024. County- and state-level summaries in this dataset are computed as the mean pixel value within each geographic boundary using area-weighted zonal statistics.", + "description": "The NOAA Weather Prediction Center HeatRisk product provides a daily, gridded (2.5 km) assessment of heat risk across the contiguous United States for the current day and 7-day forecast period. Risk is classified on a 04 scale based on the combination of heat intensity and duration relative to local historical thresholds, with consideration for overnight low temperatures and heat index. The archive provides daily GeoTIFF rasters back to August 1, 2024. County- and state-level summaries in this dataset are computed as the mean pixel value within each geographic boundary using area-weighted zonal statistics.", "standard_files": [ { "filename": "data_county.csv.gz", @@ -24794,21 +25683,21 @@ { "name": "value", "short_name": "Heat Risk Score", - "description": "Mean daily heat risk score (0–4) aggregated to county and state level.", + "description": "Mean daily heat risk score (04) aggregated to county and state level.", "measure_type": "Index", - "unit": "Score (0–4)" + "unit": "Score (04)" }, { "name": "forecast_day", "short_name": "Forecast day", - "description": "0 = historical archive (observed Day 1), 1–7 = number of days ahead in the current forecast.", + "description": "0 = historical archive (observed Day 1), 17 = number of days ahead in the current forecast.", "measure_type": "Integer", "unit": "Days" }, { "name": "low_coverage_flag", "short_name": "Low coverage flag", - "description": "1 if fewer than 9 grid pixels cover the county (~<56 km²), 0 otherwise.", + "description": "1 if fewer than 9 grid pixels cover the county (~<56 km), 0 otherwise.", "measure_type": "Binary", "unit": "Binary indicator" } @@ -24834,14 +25723,14 @@ { "name": "value", "short_name": "Heat Risk Score", - "description": "Mean daily heat risk score (0–4) aggregated to county and state level.", + "description": "Mean daily heat risk score (04) aggregated to county and state level.", "measure_type": "Index", - "unit": "Score (0–4)" + "unit": "Score (04)" }, { "name": "forecast_day", "short_name": "Forecast day", - "description": "0 = historical archive (observed Day 1), 1–7 = number of days ahead in the current forecast.", + "description": "0 = historical archive (observed Day 1), 17 = number of days ahead in the current forecast.", "measure_type": "Integer", "unit": "Days" } @@ -24849,81 +25738,6 @@ } ] }, - "NREVSS": { - "name": "NREVSS", - "display_name": "NREVSS", - "description": "The National Respiratory and Enteric Virus Surveillance System (NREVSS) is a voluntary, laboratory-based surveillance system that monitors temporal and geographic trends for respiratory syncytial virus (RSV), human parainfluenza viruses, respiratory adenoviruses, human metapneumovirus, human coronaviruses, and rotavirus circulation in the United States. Participating laboratories report weekly to CDC on the number of tests performed and the number positive for each virus. NREVSS data are used to characterize seasonal patterns of these viruses and to help public health officials anticipate and prepare for outbreaks. Data are aggregated at the HHS regional and national levels. The system has been operational since 1987 and includes approximately 300 participating laboratories across the United States.", - "standard_files": [ - { - "filename": "data.csv.gz", - "columns": [ - { - "name": "source", - "short_name": "Source", - "description": "Data source", - "measure_type": "", - "unit": "categorical" - }, - { - "name": "geography", - "short_name": "Geography", - "description": "FIPS code identifier (00 = national, 2-digit = state, 5-digit = county)", - "measure_type": "identifier", - "unit": "FIPS code" - }, - { - "name": "time", - "short_name": "Time", - "description": "Date in MM-DD-YYYY format (Saturday for weekly data)", - "measure_type": "date", - "unit": "date" - }, - { - "name": "scaled_cases", - "short_name": "Scale Cases", - "description": "Number of positive tests per week divided by the highest number of positive tests for that region", - "measure_type": "scaled positive tests", - "unit": "scaled number" - }, - { - "name": "pcr_detections", - "short_name": "PCR detections", - "description": "Number of positive tests per week by HHS region", - "measure_type": "Number of positive tests", - "unit": "Number" - }, - { - "name": "epiyr", - "short_name": "Epi_year", - "description": "Epidemiological year", - "measure_type": "year", - "unit": "year" - }, - { - "name": "epiwk", - "short_name": "Epi_week", - "description": "Epidemiological week", - "measure_type": "year", - "unit": "year" - }, - { - "name": "week", - "short_name": "week", - "description": "Calendar week", - "measure_type": "week", - "unit": "week" - }, - { - "name": "year", - "short_name": "year", - "description": "Calendar year", - "measure_type": "year", - "unit": "year" - } - ] - } - ] - }, "nssp": { "name": "nssp", "display_name": "NSSP", @@ -25209,7 +26023,7 @@ "description": "SchoolVaxView monitors vaccination coverage among U.S. school-aged children. Data are collected annually by states, territories, and select local jurisdictions through school vaccination assessments, which review student vaccination records at kindergarten entry. These data are made available by the CDC.", "standard_files": [ { - "filename": "data_exemptions.csv.gz", + "filename": "data.csv.gz", "columns": [ { "name": "time", @@ -25270,7 +26084,7 @@ ] }, { - "filename": "data.csv.gz", + "filename": "data_exemptions.csv.gz", "columns": [ { "name": "time", @@ -25338,7 +26152,7 @@ "description": "A comprehensive study of medical vaccine exemption rates among U.S. kindergartners from 2009-2024, published in JAMA by Kiang et al. The study compiled exemption data from all 50 U.S. states and Washington, DC, providing state- and county-level medical exemption rates for MMR vaccination. The dataset spans prepandemic (2009-2019) and postpandemic (2020-2024) periods, enabling analysis of how exemption patterns changed over time and following the COVID-19 pandemic. Medical exemptions are granted when a physician determines that vaccination poses a health risk to a specific child, distinct from religious or philosophical exemptions. Values are rounded for privacy protection. The research was conducted in collaboration with NBC News and methodology is documented in an accompanying article. Full data and code are available on GitHub.", "standard_files": [ { - "filename": "data_county.csv.gz", + "filename": "data.csv.gz", "columns": [ { "name": "geography", @@ -25367,18 +26181,11 @@ "description": "Percentage of kindergarten children with non-medical exemptions from MMR vaccination requirements", "measure_type": "Percent", "unit": "Percent" - }, - { - "name": "is_state_estimate", - "short_name": "is_state_estimate", - "description": "", - "measure_type": "", - "unit": "" } ] }, { - "filename": "data_state.csv.gz", + "filename": "data_county.csv.gz", "columns": [ { "name": "geography", @@ -25407,11 +26214,18 @@ "description": "Percentage of kindergarten children with non-medical exemptions from MMR vaccination requirements", "measure_type": "Percent", "unit": "Percent" + }, + { + "name": "is_state_estimate", + "short_name": "is_state_estimate", + "description": "", + "measure_type": "", + "unit": "" } ] }, { - "filename": "data.csv.gz", + "filename": "data_state.csv.gz", "columns": [ { "name": "geography", @@ -25498,7 +26312,7 @@ "description": "The CDC National Wastewater Surveillance System (NWSS) tracks measles virus RNA in wastewater samples from participating wastewater treatment facilities across the United States. Wastewater surveillance provides a complement to traditional clinical surveillance by detecting viral shedding in a community regardless of healthcare-seeking behavior. The measles wastewater surveillance program was expanded in response to the 2025 measles outbreak to provide early warning of community transmission. Data include detection rates (percentage of samples positive), detection counts, sample counts, and population served by participating sewersheds. Surveillance data are aggregated at state and national levels on a weekly basis. This approach can detect measles circulation before cases are clinically confirmed, supporting rapid public health response.", "standard_files": [ { - "filename": "data_county.csv.gz", + "filename": "data.csv.gz", "columns": [ { "name": "geography", @@ -25545,7 +26359,7 @@ ] }, { - "filename": "data.csv.gz", + "filename": "data_county.csv.gz", "columns": [ { "name": "geography", @@ -26017,7 +26831,7 @@ "description": "The Youth Risk Behavior Surveillance System (YRBSS) is a set of school-based surveys conducted by the CDC that monitor health-related behaviors among U.S. high school students. The biennial national, state, and local surveys provide weighted prevalence estimates of behaviors contributing to the leading causes of death and disability. Data were accessed via the YRBS Explorer API. Estimates are provided overall and stratified (separately, not crossed) by sex, race/ethnicity, and grade. Estimates that CDC suppressed (e.g., small sample sizes) are omitted rather than imputed. State estimates are available only for jurisdictions that share data with CDC; Minnesota, Oregon, and Washington are not included, and New York state excludes New York City.", "standard_files": [ { - "filename": "data_age_ethnicity.csv.gz", + "filename": "data_age.csv.gz", "columns": [ { "name": "geography", @@ -26040,13 +26854,6 @@ "measure_type": "category", "unit": "" }, - { - "name": "race_ethnicity", - "short_name": "Race/Ethnicity", - "description": "Race/ethnicity category", - "measure_type": "category", - "unit": "" - }, { "name": "pct_no_seatbelt", "short_name": "Did not always wear a seat belt", @@ -27835,7 +28642,7 @@ ] }, { - "filename": "data_age_sex.csv.gz", + "filename": "data_age_ethnicity.csv.gz", "columns": [ { "name": "geography", @@ -27859,9 +28666,9 @@ "unit": "" }, { - "name": "sex", - "short_name": "Sex", - "description": "Sex category (Male, Female, Overall)", + "name": "race_ethnicity", + "short_name": "Race/Ethnicity", + "description": "Race/ethnicity category", "measure_type": "category", "unit": "" }, @@ -29653,7 +30460,7 @@ ] }, { - "filename": "data_age.csv.gz", + "filename": "data_age_sex.csv.gz", "columns": [ { "name": "geography", @@ -29676,6 +30483,13 @@ "measure_type": "category", "unit": "" }, + { + "name": "sex", + "short_name": "Sex", + "description": "Sex category (Male, Female, Overall)", + "measure_type": "category", + "unit": "" + }, { "name": "pct_no_seatbelt", "short_name": "Did not always wear a seat belt", diff --git a/resources/sources_master.json b/resources/sources_master.json index c0fa6f108..30a271efc 100644 --- a/resources/sources_master.json +++ b/resources/sources_master.json @@ -1,4 +1,13 @@ { + "nrevss": { + "name": "National Respiratory and Enteric Virus Surveillance System (NREVSS)", + "url": "https://data.cdc.gov/resource/3cxc-4k8q", + "organization": "Centers for Disease Control and Prevention", + "organization_url": "https://www.cdc.gov/surveillance/nrevss/", + "description": "The National Respiratory and Enteric Virus Surveillance System (NREVSS) is a voluntary, laboratory-based surveillance system that monitors temporal and geographic trends for respiratory syncytial virus (RSV), human parainfluenza viruses, respiratory adenoviruses, human metapneumovirus, human coronaviruses, and rotavirus circulation in the United States. Participating laboratories report weekly to CDC on the number of tests performed and the number positive for each virus. NREVSS data are used to characterize seasonal patterns of these viruses and to help public health officials anticipate and prepare for outbreaks. Data are aggregated at the HHS regional and national levels. The system has been operational since 1987 and includes approximately 300 participating laboratories across the United States.", + "restrictions": "Public domain. CDC data is generally not subject to copyright restrictions.", + "data_source": "NREVSS" + }, "abcs": { "name": "Active Bacterial Core surveillance (ABCs)", "url": "https://www.cdc.gov/abcs/index.html", @@ -23,6 +32,18 @@ "restrictions": "Attribution required. Cite Ramirez et al. Open Forum for Infectious Diseases. 2025.", "data_source": "abcs" }, + "abcs_gas": { + "name": "Active Bacterial Core surveillance (ABCs) - Group A Streptococcus", + "url": "https://data.cdc.gov/Public-Health-Surveillance/Active-Bacterial-Core-surveillance-ABCs-Group-A-St/9y49-tura/about_data", + "organization": "Centers for Disease Control and Prevention", + "organization_url": "https://www.cdc.gov", + "location": "Active Bacterial Core surveillance (ABCs) Group A Streptococcus data on data.cdc.gov", + "location_url": "https://data.cdc.gov/resource/9y49-tura/", + "date_accessed": 2025, + "description": "CDC monitors invasive bacterial infections through Active Bacterial Core surveillance (ABCs), a population-based surveillance program for invasive bacterial diseases in selected geographic areas of the United States. This dataset reports annual data on invasive Group A Streptococcus (iGAS) disease from 1997 onwards, including case and death rates by age group, sex, and race; clinical syndrome distribution (cellulitis, bacteremia without focus, pneumonia, necrotizing fasciitis, streptococcal toxic shock syndrome); antibiotic resistance patterns; and emm type distribution among isolates. ABCs catchment areas include California, Colorado, Connecticut, Georgia, Maryland, Minnesota, New York, Oregon, and Tennessee, representing approximately 10% of the US population. Incidence rates are calculated using U.S. Census Bureau population estimates for the respective catchment areas.", + "restrictions": "Public domain. CDC data is generally not subject to copyright restrictions.", + "data_source": "abcs_gas" + }, "ahrf": { "name": "Area Health Resource File (AHRF)", "url": "https://data.hrsa.gov/topics/health-workforce/ahrf", @@ -86,7 +107,7 @@ "organization_url": "https://www.census.gov", "location": "2020 Census Urban Area to County Allocation File (XLSX)", "location_url": "https://www2.census.gov/geo/docs/reference/ua/2020_UA_COUNTY.xlsx", - "description": "The 2020 Census Urban Area to County Allocation File maps Census-defined urban areas (urbanized areas with population ≥ 50,000 and urban clusters with population 2,500–49,999) to counties. Each row represents a county-urban area intersection and includes the share of county population, land area, and housing units within that urban area. Summing across all urban areas for a county yields total percent urban. Counties not appearing in the file have no urban area and are considered 100% rural. Urban area boundaries are based on the 2020 decennial Census and reflect the updated delineation methodology that increased the minimum population threshold for urbanized areas from 50,000 to 50,000 and revised cluster definitions.", + "description": "The 2020 Census Urban Area to County Allocation File maps Census-defined urban areas (urbanized areas with population 50,000 and urban clusters with population 2,50049,999) to counties. Each row represents a county-urban area intersection and includes the share of county population, land area, and housing units within that urban area. Summing across all urban areas for a county yields total percent urban. Counties not appearing in the file have no urban area and are considered 100% rural. Urban area boundaries are based on the 2020 decennial Census and reflect the updated delineation methodology that increased the minimum population threshold for urbanized areas from 50,000 to 50,000 and revised cluster definitions.", "restrictions": "Public domain. U.S. Census Bureau data are generally not subject to copyright restrictions.", "date_accessed": 2026, "data_source": "census" @@ -96,7 +117,7 @@ "url": "https://www.census.gov/programs-surveys/acs/data.html", "organization": "U.S. Census Bureau", "organization_url": "https://www.census.gov", - "location": "Census API — ACS 5-Year Detailed Tables and Subject Tables", + "location": "Census API ACS 5-Year Detailed Tables and Subject Tables", "location_url": "https://api.census.gov/data.html", "description": "Extraction and formatting provided by Metopio, The American Community Survey (ACS) is an ongoing survey conducted by the U.S. Census Bureau that provides detailed demographic, social, economic, and housing data for communities across the United States. The 5-year estimates pool data over a 60-month period, providing greater statistical reliability for small geographic areas (including ZIP Code Tabulation Areas) at the cost of timeliness. Variables cover a broad range of social determinants of health including poverty, housing, education, employment, insurance coverage, and racial/ethnic composition. Data are retrieved via the Census Bureau's public API using the censusapi R package.", "restrictions": "Public domain. U.S. Census Bureau data are generally not subject to copyright restrictions.", @@ -176,7 +197,7 @@ "organization_url": "https://www.epic.com/", "description": "Epic Cosmos is a collaborative research platform containing de-identified patient data from over 300 million patients across more than 1,600 hospitals and health systems using Epic electronic health record systems. Data is accessed via SlicerDicer, a self-service analytics tool. The dataset includes emergency department visits, diagnoses, immunizations, laboratory results, and other clinical data. Due to privacy protections, counts fewer than 10 are suppressed and imputed. Coverage extends across all U.S. states and territories. Note that county-level and city-level stratifications could differ markedly in total sample size due to high levels of missingness of county data in some states.", "restrictions": "The data can be re-used with appropriate attribution. A suggested citation relating to this data is 'Results of research performed with Epic Cosmos were obtained from the PopHIVE platform (https://github.com/PopHIVE/Ingest).'", - "data_source": ["epic_chronic", "epic_diarrhea", "epic_hepb_vax", "epic_injury", "epic_resp_infections", "bundle_enteric_diseases", "bundle_youth_wellbeing"] + "data_source": ["epic_chronic", "epic_diarrhea", "epic_gas", "epic_hepb_vax", "epic_injury", "epic_resp_infections", "bundle_enteric_diseases", "bundle_youth_wellbeing"] }, "epic_health_alerts": { "name": "Epic Research Health Alerts", @@ -243,9 +264,9 @@ "url": "https://data.medicaid.gov/datasets?theme%5B0%5D=Quality", "organization": "Centers for Medicare & Medicaid Services (CMS)", "organization_url": "https://www.medicaid.gov", - "location": "Medicaid.gov Open Data – Quality Measures datasets (2014–2023)", + "location": "Medicaid.gov Open Data Quality Measures datasets (20142023)", "location_url": "https://data.medicaid.gov/datasets?theme%5B0%5D=Quality", - "description": "Annual state-level performance data on the Medicaid and CHIP Adult Core Set and Child Core Set quality measures, as voluntarily reported by states to CMS and analyzed by Mathematica via the Quality Measure Reporting (QMR) system. Measures span behavioral health (e.g., follow-up after ED visits for mental illness, substance use disorder treatment), primary and preventive care (e.g., well-child visits, immunizations), maternal and perinatal health (e.g., prenatal and postpartum care, low birthweight), dental health, care of chronic conditions (e.g., diabetes, asthma, hypertension), and long-term services and supports. Each annual dataset includes state rates and national 25th and 75th percentile benchmarks. Data cover federal fiscal years 2014–2023. Reporting is voluntary; not all states report all measures each year. The wide-format standard file contains one row per state-year-payer-domain combination, with each measure-statistic combination as a separate column following the naming convention medicaid_{measure_abbr}_{population}_{sub_metric}_{stat} where population is 'ch' (child) or 'ad' (adult), sub_metric captures time windows or sub-components, and stat is 'rate', 'pct_25', or 'pct_75'.", + "description": "Annual state-level performance data on the Medicaid and CHIP Adult Core Set and Child Core Set quality measures, as voluntarily reported by states to CMS and analyzed by Mathematica via the Quality Measure Reporting (QMR) system. Measures span behavioral health (e.g., follow-up after ED visits for mental illness, substance use disorder treatment), primary and preventive care (e.g., well-child visits, immunizations), maternal and perinatal health (e.g., prenatal and postpartum care, low birthweight), dental health, care of chronic conditions (e.g., diabetes, asthma, hypertension), and long-term services and supports. Each annual dataset includes state rates and national 25th and 75th percentile benchmarks. Data cover federal fiscal years 20142023. Reporting is voluntary; not all states report all measures each year. The wide-format standard file contains one row per state-year-payer-domain combination, with each measure-statistic combination as a separate column following the naming convention medicaid_{measure_abbr}_{population}_{sub_metric}_{stat} where population is 'ch' (child) or 'ad' (adult), sub_metric captures time windows or sub-components, and stat is 'rate', 'pct_25', or 'pct_75'.", "restrictions": "Public domain. CMS/Medicaid.gov data is generally not subject to copyright restrictions.", "date_accessed": 2025, "data_source": ["medicaid_quality", "bundle_maternal_health", "bundle_youth_wellbeing"] @@ -319,7 +340,7 @@ "date_accessed": 2025, "organization": "National Center for Health Statistics (NCHS)", "organization_url": "https://www.cdc.gov/nchs/", - "description": "The National Center for Health Statistics (NCHS) houses the the Vital Statistics Rapid Release (VSRR) program. The program reports monthly deaths from drug overdose at the state level and quarterly deaths from drug overdose at the county level, as well as quarterly age-adjusted mortality rates for 21 selected causes of death at the state level. Rates are expressed as per 100,000 people. Counts of 1–9 deaths are suppressed to protect privacy and imputed as 5; the suppressed_flag column identifies these records. Data from the VSSR program and are provisional, meaning they are subject to revision as more death certificates are received and processed. New York City and New York State are combined.", + "description": "The National Center for Health Statistics (NCHS) houses the the Vital Statistics Rapid Release (VSRR) program. The program reports monthly deaths from drug overdose at the state level and quarterly deaths from drug overdose at the county level, as well as quarterly age-adjusted mortality rates for 21 selected causes of death at the state level. Rates are expressed as per 100,000 people. Counts of 19 deaths are suppressed to protect privacy and imputed as 5; the suppressed_flag column identifies these records. Data from the VSSR program and are provisional, meaning they are subject to revision as more death certificates are received and processed. New York City and New York State are combined.", "restrictions": "Public domain. CDC/NCHS data is generally not subject to copyright restrictions.", "data_source": "nchs_mortality" }, @@ -329,7 +350,7 @@ "date_accessed": 2025, "organization": "National Center for Health Statistics (NCHS)", "organization_url": "https://www.cdc.gov/nchs/", - "description": "Rates are expressed as per 100,000 people. Counts of 1–9 deaths are suppressed to protect privacy and imputed as 5; the suppressed_flag column identifies these records.", + "description": "Rates are expressed as per 100,000 people. Counts of 19 deaths are suppressed to protect privacy and imputed as 5; the suppressed_flag column identifies these records.", "restrictions": "Public domain. CDC/NCHS data is generally not subject to copyright restrictions.", "data_source": "nchs_mortality" }, @@ -360,7 +381,7 @@ "url": "https://www.nhtsa.gov/file-downloads?p=nhtsa/downloads/FARS/", "organization": "National Highway Traffic Safety Administration (NHTSA)", "organization_url": "https://www.nhtsa.gov/", - "location": "NHTSA File Downloads — FARS National CSV archives", + "location": "NHTSA File Downloads FARS National CSV archives", "location_url": "https://www.nhtsa.gov/file-downloads?p=nhtsa/downloads/FARS/", "description": "FARS is a nationwide census providing NHTSA, Congress, and the American public with yearly data on fatal injuries suffered in motor vehicle traffic crashes. FARS contains data on all crashes in the United States involving a fatality in a motor vehicle traffic crash on a public road. A fatal crash is one in which a motor vehicle is involved and at least one person dies within 30 days of the crash. Data are collected from police crash reports, state vehicle registration files, state driver licensing files, state highway department data, vital statistics, and other sources. FARS has been operational since 1975 and covers all 50 states, the District of Columbia, and Puerto Rico (national files cover the 50 states and DC).", "restrictions": "Public domain. NHTSA data is generally not subject to copyright restrictions.", @@ -392,20 +413,11 @@ "organization_url": "https://www.wpc.ncep.noaa.gov/", "location": "HeatRisk GeoTIFF Archive and 7-Day Forecast", "location_url": "https://www.wpc.ncep.noaa.gov/heatrisk/data.html", - "description": "The NOAA Weather Prediction Center HeatRisk product provides a daily, gridded (2.5 km) assessment of heat risk across the contiguous United States for the current day and 7-day forecast period. Risk is classified on a 0–4 scale based on the combination of heat intensity and duration relative to local historical thresholds, with consideration for overnight low temperatures and heat index. The archive provides daily GeoTIFF rasters back to August 1, 2024. County- and state-level summaries in this dataset are computed as the mean pixel value within each geographic boundary using area-weighted zonal statistics.", + "description": "The NOAA Weather Prediction Center HeatRisk product provides a daily, gridded (2.5 km) assessment of heat risk across the contiguous United States for the current day and 7-day forecast period. Risk is classified on a 04 scale based on the combination of heat intensity and duration relative to local historical thresholds, with consideration for overnight low temperatures and heat index. The archive provides daily GeoTIFF rasters back to August 1, 2024. County- and state-level summaries in this dataset are computed as the mean pixel value within each geographic boundary using area-weighted zonal statistics.", "restrictions": "Public domain. NOAA data is generally not subject to copyright restrictions.", "date_accessed": 2026, "data_source": ["noaa_heat_risk", "bundle_youth_wellbeing"] }, - "nrevss": { - "name": "National Respiratory and Enteric Virus Surveillance System (NREVSS)", - "url": "https://data.cdc.gov/resource/3cxc-4k8q", - "organization": "Centers for Disease Control and Prevention", - "organization_url": "https://www.cdc.gov/surveillance/nrevss/", - "description": "The National Respiratory and Enteric Virus Surveillance System (NREVSS) is a voluntary, laboratory-based surveillance system that monitors temporal and geographic trends for respiratory syncytial virus (RSV), human parainfluenza viruses, respiratory adenoviruses, human metapneumovirus, human coronaviruses, and rotavirus circulation in the United States. Participating laboratories report weekly to CDC on the number of tests performed and the number positive for each virus. NREVSS data are used to characterize seasonal patterns of these viruses and to help public health officials anticipate and prepare for outbreaks. Data are aggregated at the HHS regional and national levels. The system has been operational since 1987 and includes approximately 300 participating laboratories across the United States.", - "restrictions": "Public domain. CDC data is generally not subject to copyright restrictions.", - "data_source": "NREVSS" - }, "nssp": { "name": "National Syndromic Surveillance Program (NSSP)", "location": "National Syndromic Surveillance Program",