Sources of racial disparities in HIV prevalence in men who have sex with men in Atlanta, GA, USA: A modeling study
Steven Goodreau, Ph.D.
University of Washington, Seattle
Black men who have sex men (MSM) in the US have a substantially higher prevalence of infection than White MSM, and many proximal and distal explanations have been offered to account for pieces of this disparity.
We created a simulation model to assess the strength of existing hypotheses and data. We built a dynamic, stochastic, agent-based network model of Black and White MSM aged 18–39 years in Atlanta, that incorporated race-specific individual and dyadic-level prevention and risk behaviors, network attributes, and care patterns. We estimated parameters from two Atlanta-based studies in this population (n=1117), supplemented by other published work. We modeled the ability for racial assortativity to generate or sustain disparities in the prevalence of HIV infection, alone or in conjunction with scenarios of observed racial patterns in behavioral, care, and susceptibility parameters.
Race-assortative mixing alone could not sustain a pre-existing disparity in prevalence of HIV between Black and White MSM. Differences in care cascade, stigma-related behaviors, and CCR5 genotype each contributed substantially to the disparity (explaining 10.0%, 12.7%, and 19.1% of the disparity, respectively), but nearly half (44.5%) could not be explained by the factors investigated. A scenario assessing race-specific reporting differences in risk behavior was the only one to yield a prevalence in black MSM (44.1%) similar to that observed (43.4%). Racial assortativity is an inadequate explanation for observed disparities. Work to close the gap in the care cascade by race is imperative, as are efforts to increase serodiscussion and strengthen relationships among Black MSM particularly. Further work is urgently needed to identify other sources of, and pathways for, this disparity, to integrate concomitant epidemics into models, and to understand reasons for racial differences in behavioral reporting.