This repository is for the Sunbelt 2025 workshop on epiworldR. Here is the description from the Sunbelt website:
This workshop introduces epiworldR, an R package with a fast (C++ backend) and highly customizable framework for building network-based transmission/diffusion agent-based models (ABM). These models provide valuable information that may aid in performing complex simulation studies and make informed, evidence-based policy decisions for the general population. epiworldR is a flexible tool that can capture the complexity of transmission/diffusion dynamics resulting from agents’ heterogeneity, network structure, transmission dynamics, environmental factors (e.g., policies), and many other elements. Some key features of epiworldR are the ability to construct multi-disease models (e.g., models of competing multi-pathogens/multi-rumor), design mutating pathogens, architect population- level interventions, and build models with an arbitrary number of compartments/states (beyond SIR/SEIR). Moreover, epiworldR is really fast. For example, simulating a SIR model with 100,000 agents for 100 days takes less than ⅓ of a second (about three times faster than most popular packages).
The workshop will be 100% hands-on. It will feature examples of simulating multi- disease/rumor models, policy intervention models, and mutating variants. You can learn more about what to expect by visiting https://uofuepibio.github.io/epiworldR-workshop/. Participants should have a working knowledge of R (e.g., some experience with statnet). We will be using the latest version of epiworldR and will also provide a cloud environment with all the required components for the workshop.
To get started, install the latest stable version of epiworldR from CRAN:
install.packages("epiworldR")or the latest development version from GitHub:
devtools::install_github("UofUEpiBio/epiworldR")Andrew Pulsipher (@apulsipher) is a software developer in the Division of Epidemiology at the University of Utah's School of Medicine.
Dr. George G. Vega Yon (@gvegayon) is a Research Assistant Professor of Epidemiology at the University of Utah's School of Medicine. You can learn more about Dr. Vega Yon's research here: https://ggvy.cl.