Mathematical Modeling of Infectious Disease Dynamics
EpiModel is an R package that provides tools for simulating and analyzing mathematical models of infectious disease dynamics. Supported epidemic model classes include deterministic compartmental models, stochastic individual contact models, and stochastic network models. Disease types include SI, SIR, and SIS epidemics with and without demography, with utilities available for expansion to construct and simulate epidemic models of arbitrary complexity. The network model class is based on the statistical framework of temporal exponential random graph models (ERGMs) implementated in the Statnet suite of software for R.
The current software version is EpiModel v2.3.1, which may be downloaded from CRAN and installed in R through:
The development version of EpiModel is hosted on GitHub and may be installed via the remotes package by:
install.packages("EpiModel", dependencies = TRUE)
The software source code is available at the Github Repository. Users should submit bug reports and feature requests as issues there. The Releases page on the repository lists all the changes to the software over time.
EpiModel 2.0 Update
In July 2020, we relased EpiModel version 2.0. This major software package update incorporates a substantial redesign of many elements of the EpiModel infrastructure and application programming interface (API). We anticipate that there will be some minor backwards incompatibilities with any EpiModel code developed with versions 1.x. There is a EpiModel 2.0 migration document available in the Tutorials page.
If using EpiModel for teaching or research, please include a citation of our software with:
Jenness SM, Goodreau SM and Morris M. EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks. Journal of Statistical Software. 2018; 84(8): 1-47.
The EpiModel Software Manual provides a list of all the main functions within the package, with syntax and examples. This documentation is also available within the package by consulting the help files.
A good place to start learning about EpiModel is our main methods paper published in the Journal of Statistical Software. It is available at http://doi.org/10.18637/jss.v084.i08.
Tutorials and Workshops
The Tutorials page provides introductions to running epidemic models of the three classes supported in EpiModel, and then expanding those models to address novel research questions. For greater theoretical background to fitting stochastic network models specifically, consult the Workshops page to view the materials from our in-person courses on using EpiModel.
We recently started a new EpiModel Gallery that contains templates of extensions to EpiModel, for now focused on network-based mathematical models. We will be continuing to add new examples to the gallery, and encourage users to either file requests for new examples or contribute them following our guidelines.
NME is a 5-day short course at the University of Washington that provides an introduction to stochastic network models for infectious disease transmission dynamics, with a focus on empirically based modeling of HIV, STIs, and other close-contact infectious diseases. For more information on how to apply for the course, see our course website.