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Workshop Title
Network Modeling for Infectious Disease Dynamics
Instructor
Samuel M. Jenness, PhD MPH
Assistant Professor, Department of Epidemiology
PI, EpiModel Research Lab
Rollins School of Public Health, Emory University
Bio
Samuel M. Jenness, PhD is an Assistant Professor in the Department of Epidemiology at the Rollins School of Public Health at Emory University. He received his PhD in Epidemiology at the University of Washington. At Emory, he leads the EpiModel Research Lab, which focuses on developing the methods and software tools for mathematical modeling of infectious diseases over complex networks. He has applied these approaches to investigate HIV and STI transmission dynamics and emerging prevention technologies such as HIV preexposure prophylaxis and medical male circumcision in highly impacted populations, including men who have sex with men in the United States and heterosexual couples in Sub-Saharan Africa.
Workshop Summary
This workshop will introduce new tools for network-based mathematical modeling of infectious disease transmission dynamics with the EpiModel software package in R. EpiModel (www.epimodel.org) is an open-source R package that builds upon the robust Statnet suite of software for representing, modeling, and visualizing network data. In this workshop, I will first provide an overview of epidemic modeling methods for infectious diseases, with a primary motivation to demonstrate why representing highly structured sexual partnership networks is important for HIV/STI transmission and how that may be done within epidemic models. Workshop participants will learn the statistical methods of exponential random graph models (ERGMs) for modeling and simulating dynamic networks using easy-to-collect empirical data, then how ERGMs are used within EpiModel’s infectious disease simulation engine. This workshop will be hands-on and interactive: we will fit models and run epidemic simulations together to collectively investigate how network, biological, and demographic parameters impact epidemiological outputs for basic disease types (SI/SIS/SIR). I will close by showing how EpiModel may be extended in a modular way to address novel research questions and complex diseases.
Participants are recommended to bring a laptop with R and Rstudio installed (instructions here: http://statnet.github.io/nme/prep-inst.html). While prior knowledge and experience with programming in R may be helpful in getting the most out of the interactive exercises, it is not a prerequisite and workshop code can be run by R beginners. Additionally, while the content is focused on infectious disease, the same methods may be used to model social diffusion and related “contagion” processes across networks, so those interested in agent-based modeling more broadly are encouraged to attend.