Mathematical models for infectious disease transmission dynamics over networks: statistical methods, software tools, and applications for HIV/STI prevention science
Samuel Jenness, Ph.D.
HIV and STIs are transmitted over highly structured sexual partnership networks that evolve over time. Investigating network-based drivers of epidemics and opportunities for disease prevention has required the development of statistical approaches to modeling dynamic network structures embedded within broader mathematical models of intra- and inter-host epidemiology, demography, and bio-behavioral disease risk. In this talk, I present on temporal exponential random graph models (ERGMs) to model dynamic networks using easily collected egocentric network data, the integration of these methods within our epidemic modeling software, EpiModel (www.epimodel.org), and our recent applications of these tools to investigate empirical and intervention questions for HIV/STI prevention among men who have sex with men in the United States.