Modeling the Impact of Post-Diagnosis Behavior Change on HIV Prevalence in Southern California Men Who Have Sex with Men (MSM)

Aditya Khanna, University of Washington
Steven M. Goodreau, University of Washington
Pamina Gorbach, University of California, Los Angeles

Our objective is to demonstrate the population level effects of individual-level post-diagnosis behavior change (PDBC) in Southern California 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. We use behavioral data from the Southern California Acute Infection and Early Disease Research Program (AIEDRP) and biological data from a number of published sources. We create network models derived from the exponential random graph model (ERGM) family. Our models incorporate vital processes of birth, death, and aging, and other related epidemiological processes, namely, circumcision-status, testing behavior, treatment, meth use, diagnosis status, partnership types, viral load, and sexual role. We find that without PDBC HIV prevalence among MSM would be significantly higher at any reasonable frequency of testing. We also demonstrate that cross-sectional data cannot capture the effects of PDBC and longitudinal data are needed.