multigroup.vaccine

Overview

multigroup.vaccine models infectious disease dynamics in populations with multiple distinct subgroups that can have:

• Different vaccination rates
• Different susceptibility and/or transmissibility characteristics
• Different contact rates and patterns between and within groups

The package provides both an interactive shiny dashboard for a simple two-group example and programmatic R functions for epidemiological modeling and outbreak forecasting.

Installation

From CRAN (recommended)(when available)

install.packages("multigroup.vaccine")

From R-universe

install.packages("multigroup.vaccine", 
                 repos = "https://epiforesite.r-universe.dev")

From GitHub

# install.packages("remotes")
remotes::install_github("EpiForeSITE/multigroup-vaccine")

Dependencies

The package depends on the following R packages:

• Imports: deSolve, graphics, shiny, stats, bslib (>= 0.9.0), htmltools, socialmixr
• Suggests: knitr, rmarkdown, testthat (>= 3.0.0)

Quick Start

Interactive Dashboard

Launch the shiny dashboard for interactive modeling:

library(multigroup.vaccine)
run_my_app()

The dashboard models two distinct sub-populations with differential within-group and across-group contact rates and different vaccination adherence levels. See Nguyen et al. (2024) and Duong et al. (2026) for more details on this modeling approach.

Programmatic Usage

You can also use the package functions directly in R scripts. Here’s an example of comparing populations with different vaccination rates:

Two-Group Population Comparison

# Compare two populations with different vaccination rates
results <- finalsize(
  popsize = c(10000, 10000),         # Equal population sizes
  R0 = 2,                            # Basic reproduction number
  contactmatrix = matrix(1, 2, 2),   # Equal and symmetric group-to-group contact 
  relsusc = c(1, 1),                 # Equal group susceptibility per at-risk contact
  reltransm = c(1, 1),               # Equal group transmissibility per at-risk contact
  initR = c(0, 0),                   # Initially none previously infected & immune (R)
  initI = c(1, 0),                   # One initial infectious case (I) in first group
  initV = c(1000, 2000),             # Initial numbers immune by vaccination (V)
  method = "analytic"                # Solve for final size analytically
)
print(results)

For examples of other functions or more complex scenarios, see the package vignettes.

Features

• Multi-group SIR modeling with vaccination and variable contact rates
• Age-structured population models using census data
• Contact matrix integration via POLYMOD-derived and custom matrices
• Final outbreak size calculations using both analytic and stochastic methods
• Interactive shiny dashboard for scenario exploration

Documentation

Comprehensive documentation and vignettes are available at: https://epiforesite.github.io/multigroup-vaccine/

View all available vignettes:

browseVignettes("multigroup.vaccine")

Core Functions

• finalsize(): Master function for final outbreak size calculations and simulations
• contactMatrixPropPref(): Generate contact matrices from proportionate mixing and preferential contact assumptions
• contactMatrixPolymod(): Generate age-structured contact matrices from POLYMOD data
• getCensusData(): Download and process US Census Bureau population data for age group-structured models
• run_my_app(): Launch the interactive shiny dashboard for a two-group model

Getting Help

• Bug reports: GitHub Issues
• Documentation: Package website

Citation

If you use this package in your research, please obtain citation information in R:

citation("multigroup.vaccine")

Development Setup

For local development:

# Clone the repository
# git clone https://github.com/EpiForeSITE/multigroup-vaccine.git

# Install development dependencies
install.packages(c("devtools", "roxygen2", "pkgdown", "lintr"))

# Load the package for development
devtools::load_all()

# Run tests
devtools::test()

# Check package
devtools::check()

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

Acknowledgments

This package is part of the EpiForeSITE software ecosystem developed by the ForeSITE Group at the University of Utah. Development was supported by the Centers for Disease Control and Prevention’s Center for Forecasting and Outbreak Analytics (Cooperative agreement CDC-RFA-FT-23-0069).