imuGAP provides a fitting and imputation / prediction tool for a particular process model of vaccination uptake. The tool provides flexible trends and relationships for the elements of the process.
Model
The imuGAP sampler fits two model effects: a lifetime tendency towards vaccination and a time varying force of vaccination. To fit those effects, the model evaluates observations which may combine many populations. The model distinguishes populations by place, birth timing, and age.
The model organizes places into a hierarchy, for example a state which contains counties which in turn contain cities. The effects in a particular place combine the impact of all enclosing locations.
Installation
# Install from GitHub
remotes::install_github("ACCIDDA/imuGAP")Requires R >= 4.1.0 and a C++ toolchain (for Stan model compilation).
CLI Usage
After installing the package, set up the command-line interface:
imuGAP::install_cli()This creates a symlink at ~/.local/bin/imugap. Make sure ~/.local/bin is on your PATH.
You only need to run install_cli() once after installing or updating the package; it refreshes the symlink so it points at the current install.
Commands
# Show help
imugap -h
# Validate input data (dry run, no model fitting)
imugap -h <input_dir>
# Run model fitting
imugap <input_dir> [output_dir]output_dir defaults to input_dir if not specified. Output is a fit.rds file containing the raw stanfit object.
Input Files
input_dir must contain three files (CSV or RDS):
| File | Columns | Description |
|---|---|---|
observations |
obs_id, positive, sample_n
|
School-level vaccination counts. |
populations |
obs_id, loc_id, cohort, age, dose, weight
|
Observation metadata. Weights must sum to 1 per obs_id. dose must include both 1 and 2. |
locations |
loc_id, parent_id
|
Location hierarchy (state > county > school). Root has parent_id = NA. |