Ending the HIV epidemic in Chicago: Evidence from high-fidelity local agent-based model

Wouter Vermeer, PhD
Northwestern University

Nanette Benbow, M.A.S.
Northwestern University

ABSTRACT:
Agent-based models have enormous potential for modeling complex social phenomena. The ability to model complex individual-level social dynamics and project system-wide behaviors can help inform decision makers in their effort to curb a phenomenon like the spread of HIV. To produce actionable results, models need to accurately capture the dynamics and behaviors observed by decision makers. As such, models aimed at supporting decision making need to be tailored to the local context by incorporating behaviors based on local data. In this presentation we describe our model for HIV-spread in Chicago and highlight how we used Chicago-level data and input from local public health experts to inform this model. We will illustrate how our model can be used to perform predictive scenario analysis and discuss how these results can be used to inform decision makers as they plan their HIV care and prevention strategies to end the HIV epidemic.