324 min dis

scripts/FQHCmindis.R

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+# Author: Mahjabin Kabir Adrita
+# Date: 2026-08-02
+# Data Source: Substance Abuse and Mental Health Services Administration (SAMHSA)
+
+# Load required libraries
+
+library(sf)
+library(tmap)
+library(units)
+library(dplyr)
+
+
+# 1. Read tract level geojson
+
+Boundary <- st_read("https://herop-geodata.s3.us-east-2.amazonaws.com/census/tract-2020-500k.geojson")
+
+# Transform tracts to Illinois State Plane (Meters)
+Boundary <- st_transform(Boundary, 5070)
+
+
+# 2. Read Fqhc Clinics from CSV
+#    (CSV must have latitude & longitude)
+
+Fqhc_csv <- read.csv("C:/Users/adrit/Downloads/FQHC (2).csv")
+
+# Expected columns:
+# Fqhc_csv$longitude
+# Fqhc_csv$latitude
+head(Fqhc_csv)
+
+Fqhc_csv_clean <- Fqhc_csv %>%
+  dplyr::filter(!is.na(Longitude) & !is.na(Latitude))
+
+
+FqhcSf <- st_as_sf(
+  Fqhc_csv_clean,
+  coords = c("Longitude", "Latitude"),
+  crs = 4326,
+  remove = FALSE
+)
+
+Fqhc_csv$coord_status <- ifelse(
+  is.na(Fqhc_csv$Longitude) | is.na(Fqhc_csv$Latitude),
+  "Missing coordinates",
+  "Valid coordinates"
+)  
+
+# Convert CSV to sf point object (WGS84)
+FqhcSf <- st_as_sf(
+  Fqhc_csv_clean,
+  coords = c("Longitude", "Latitude"),
+  crs = 4326,
+  remove = FALSE
+)
+
+# Transform clinics to match ZIP CRS
+FqhcSf <- st_transform(FqhcSf, 5070)
+
+# ===============================
+# 3. Quick data checks
+# ===============================
+st_crs(Boundary)
+st_crs(FqhcSf)
+
+# ===============================
+# 4. Visualize ZIPs and Clinics
+# ===============================
+library(tmap)
+
+tmap_mode("plot")
+
+tm_shape(Boundary) +
+  tm_polygons(
+    col = "lightblue",
+    border.col = "blue",
+    lwd = 0.05,
+    alpha = 0.35,
+    title = "Census tracts"
+  ) +
+  tm_shape(FqhcSf) +
+  tm_dots(
+    col = "red",
+    size = 0.02,
+    alpha = 0.8,
+    title = "Fqhc clinics"
+  ) +
+  tm_layout(
+    main.title = "Fqhc Clinics vs Census Tracts (US)",
+    main.title.position = "center",
+    legend.outside = TRUE,
+    frame = FALSE
+  )
+
+# ===============================
+# 5. Create ZIP centroids
+
+BoundaryCentroids <- st_centroid(Boundary)
+
+
+# 6. Find nearest clinic to each ZIP centroid
+
+nearestClinic_idx <- st_nearest_feature(
+  BoundaryCentroids,
+  FqhcSf
+)
+
+nearestClinic <-FqhcSf[nearestClinic_idx, ]
+
+
+# 7. Calculate distance (Meters → miles)
+
+minDist_m <- st_distance(
+  BoundaryCentroids,
+  nearestClinic,
+  by_element = TRUE
+)
+
+# Convert to miles
+minDist_mi <- set_units(minDist_m, "mi")
+
+
+# 8. Attach distances back to ZIP polygons
+
+minDistSf <- Boundary  %>%
+  mutate(FqhcMinDis = as.numeric(minDist_mi))
+
+
+# 9. Map results
+tmap_mode("plot")
+
+tm_shape(minDistSf) +
+  tm_polygons(
+    "FqhcMinDis",
+    style = "quantile",
+    n = 7,
+    palette = "viridis",
+    lwd = 0,             
+    border.alpha = 0,
+    alpha = 0.95,
+    colorNA = "grey90",
+    title = "Minimum Distance (miles)"
+  ) +
+  tm_layout(
+    main.title = "Minimum Distance from Tract Centroid to Fqhc Clinic",
+    main.title.position = "center",
+    legend.outside = TRUE,
+    frame = FALSE
+  )
+# 10. Export results
+
+
+# Save attribute table as CSV (geometry dropped)
+write.csv(
+  st_drop_geometry(minDistSf),
+  "C:/Users/adrit/Downloads/FqhcMinimumDistance-2025.csv",
+  row.names = FALSE
+)
+
+# Save full spatial layer as GeoJSON (keeps geometry)
+st_write(
+  minDistSf,
+  "C:/Users/adrit/Downloads/FqhcMinimumDistance-2025.geojson",
+  driver = "GeoJSON",
+  delete_dsn = TRUE
+)
+

scripts/HCVmindis.R

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+# Author: Mahjabin Kabir Adrita
+# Date: 2026-08-02
+# Data Source: Substance Abuse and Mental Health Services Administration (SAMHSA)
+
+# Load required libraries
+
+library(sf)
+library(tmap)
+library(units)
+library(dplyr)
+
+
+# 1. Read tract level geojson
+
+Boundary <- st_read("https://herop-geodata.s3.us-east-2.amazonaws.com/census/tract-2020-500k.geojson")
+
+# Transform tracts to Illinois State Plane (Meters)
+Boundary <- st_transform(Boundary, 5070)
+
+
+# 2. Read Hcv Clinics from CSV
+#    (CSV must have latitude & longitude)
+
+Hcv_csv <- read.csv("C:/Users/adrit/Downloads/HCV.csv")
+
+# Expected columns:
+# Hcv_csv$longitude
+# Hcv_csv$latitude
+head(Hcv_csv)
+# Convert CSV to sf point object (WGS84)
+HcvSf <- st_as_sf(
+  Hcv_csv,
+  coords = c("longitude", "latitude"),
+  crs = 4326,
+  remove = FALSE
+)
+
+# Transform clinics to match ZIP CRS
+HcvSf <- st_transform(HcvSf, 5070)
+
+# ===============================
+# 3. Quick data checks
+# ===============================
+st_crs(Boundary)
+st_crs(HcvSf)
+
+# ===============================
+# 4. Visualize ZIPs and Clinics
+# ===============================
+library(tmap)
+
+tmap_mode("plot")
+
+tm_shape(Boundary) +
+  tm_polygons(
+    col = "lightblue",
+    border.col = "blue",
+    lwd = 0.05,
+    alpha = 0.35,
+    title = "Census tracts"
+  ) +
+  tm_shape(HcvSf) +
+  tm_dots(
+    col = "red",
+    size = 0.02,
+    alpha = 0.8,
+    title = "Hcv clinics"
+  ) +
+  tm_layout(
+    main.title = "Hcv Clinics vs Census Tracts (US)",
+    main.title.position = "center",
+    legend.outside = TRUE,
+    frame = FALSE
+  )
+
+# ===============================
+# 5. Create ZIP centroids
+
+BoundaryCentroids <- st_centroid(Boundary)
+
+# Optional geometry check
+plot(st_geometry(Boundary), col = "grey90", border = "grey80", lwd = 0.1)
+plot(st_geometry(BoundaryCentroids), add = TRUE, pch = 16, cex = 0.15, col = grDevices::adjustcolor("red", alpha.f = 0.4))
+
+
+# 6. Find nearest clinic to each ZIP centroid
+
+nearestClinic_idx <- st_nearest_feature(
+  BoundaryCentroids,
+  HcvSf
+)
+
+nearestClinic <-HcvSf[nearestClinic_idx, ]
+
+
+# 7. Calculate distance (Meters → miles)
+
+minDist_m <- st_distance(
+  BoundaryCentroids,
+  nearestClinic,
+  by_element = TRUE
+)
+
+# Convert to miles
+minDist_mi <- set_units(minDist_m, "mi")
+
+
+# 8. Attach distances back to ZIP polygons
+
+minDistSf <- Boundary  %>%
+  mutate(HcvMinDis = as.numeric(minDist_mi))
+
+
+# 9. Map results
+tmap_mode("plot")
+
+tm_shape(minDistSf) +
+  tm_polygons(
+    "HcvMinDis",
+    style = "quantile",
+    n = 7,
+    palette = "viridis",
+    lwd = 0,             
+    border.alpha = 0,
+    alpha = 0.95,
+    colorNA = "grey90",
+    title = "Minimum Distance (miles)"
+  ) +
+  tm_layout(
+    main.title = "Minimum Distance from Tract Centroid to Hcv Clinic",
+    main.title.position = "center",
+    legend.outside = TRUE,
+    frame = FALSE
+  )
+# 10. Export results
+
+
+# Save attribute table as CSV (geometry dropped)
+write.csv(
+  st_drop_geometry(minDistSf),
+  "C:/Users/adrit/Downloads/HCVMinimumDistance-2025.csv",
+  row.names = FALSE
+)
+
+# Save full spatial layer as GeoJSON (keeps geometry)
+st_write(
+  minDistSf,
+  "C:/Users/adrit/Downloads/HcvMinimumDistance-2025.geojson",
+  driver = "GeoJSON",
+  delete_dsn = TRUE
+)