pviem

Overview

The goal of pviem is to estimate population-level immunity to poliovirus using routine immunization, live-birth, vaccine-efficacy, and vaccination-schedule data. Its modular workflow supports different administrative and temporal scales and can be adapted to other vaccine-preventable diseases.

Installation

You can install the development version of pviem from GitHub with:

# install.packages("devtools")
devtools::install_github("SACEMA/pviem", build_vignettes = TRUE, dependencies = TRUE)

Example

This basic example combines synthetic Fakeland boundaries and routine immunization data with literature-derived vaccine efficacy estimates included in the package. It illustrates the workflow; the synthetic country data should not be used to support scientific or public-health decisions.

For a guided introduction, read the vignettes in this order: setup, data requirements, getting started, and the detailed workflow.

library(pviem)
library(dplyr)

config_pviem(admin = c("prov_code", "dist_code"))

immunity_n <- compute_immunity_samples(
  n_samples = 5,
  ri_data = dummy_yearly_ri_data,
  vs_info = prep_dummy_vs_info,
  efficacy = prep_dummy_efficacy,
  birth_seasonality = dummy_birth_seasonality,
  neighbors = get_neighbors(fakeland, admin_cols = c("admin1_code", "admin2_code")),
  max_level = 3,
  imputation_mode = "stochastic",
  sample_mode = "uniform",
  seed = 42
) %>%
  summarize_immunity_samples() %>%
  mutate(type = factor(type, levels = c("mucosal", "humoral")))

We can visualize the mean estimate and empirical interval across imputation samples for selected districts. Five samples keep this README example fast but are not sufficient for stable uncertainty estimates; use many more samples in a real analysis.

library(ggplot2)

imm_color_scheme <- c(
  mucosal = "#0072B2",
  humoral = "#D55E00"
  # mucosal = "#66a61e",
  # humoral = "#7570b3"
)

immunity_n[
  dist_code %in% c("A01", "B01", "C01", "D01") & serotype == "PV1"
] |>
  ggplot(aes(x = year, y = .mean, color = type, fill = type)) +
  geom_line() +
  geom_point(size = .75) +
  geom_errorbar(aes(ymin = .lower, ymax = .upper), width = 0.25, linewidth = 0.5) +
  facet_wrap(~dist_code, scales = "free_y") +
  scale_x_continuous(breaks = scales::breaks_width(2)) +
  scale_color_manual(values = imm_color_scheme) +
  scale_fill_manual(values = imm_color_scheme) +
  theme_minimal() +
  labs(
    title = "PV1 immunity estimates in some districts of Fakeland",
    subtitle = "Mean and empirical 95% interval by birth cohort",
    x = "Birth year",
    y = "Immunity",
    color = "Immunity type",
    fill = "Immunity type"
  )

Getting help

If you encounter a bug, please file an issue with a minimal reproducible example on GitHub. Feedback from applications to other vaccine-preventable diseases is also welcome.