Modeling the impact of post-diagnosis behavior change on HIV prevalence in Southern California men who have sex with men (MSM).

Our objective here is to demonstrate the population-level effects of individual-level post-diagnosis behavior change (PDBC) in Southern Californian men who have sex with men (MSM), recently diagnosed with HIV. While PDBC has been empirically documented, the population-level effects of such behavior change are largely unknown. To examine these effects, we develop network models derived from the exponential random graph model family. We parameterize our models using behavioral data from the Southern California Acute Infection and Early Disease Research Program, and biological data from a number of published sources. Our models incorporate vital demographic processes, biology, treatment and behavior. We find that without PDBC, HIV prevalence among MSM would be significantly higher at any reasonable frequency of testing. We also demonstrate that higher levels of HIV risk behavior among HIV-positive men relative to HIV-negative men observed in some cross-sectional studies are consistent with individual-level PDBC.