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Simulating Complex Agent-Based Model with epiworldR: A fast and flexible ABM framework

This repository is for the Sunbelt 2023 workshop about epiworldR. Here is the description from the Sunbelt website:

Despite significant medical advances, infectious diseases continue to prevail worldwide, accounting for over 17 million deaths yearly (WHO). This workshop introduces epiworldR, an R package that provides a fast (C++ backend) and highly-customizable framework for building network-based transmission/diffusion agent-based models [ABM]. This package provides valuable information that may aid in making informed, evidence-based policy decisions for the general population and performing complex simulation studies. epiworldR delivers a flexible tool that can capture transmission/diffusion dynamics complexity 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.

The workshop will be 100% hands-on and will feature examples of simulating multi-disease/rumor models, policy intervention models, mutating variants, and creating models with arbitrary compartments. Participants should have a working knowledge of R (e.g., some experience with statnet).

Workshop materials

To get started, you are invited to download and install the latest version of epiworldR. You can do so by running the following code in R:

devtools::install_github("UofUEpiBio/epiworldR")

A version of the R package will be available on CRAN soon.

About the instructors

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.

Derek Meyer (@derekmeyer37) is a graduate student in the Department of Public Health Sciences at the University of Utah.