We built a dynamic, stochastic, agent-based network model of black and white MSM aged 18-39 years in Atlanta, GA, USA, that incorporated race-specific individual and dyadic-level prevention and risk behaviours, network attributes, and care patterns. We estimated parameters from two Atlanta-based studies in this population (n=1117), supplemented by other published work. We modelled 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 behavioural, care, and susceptibility parameters.
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 behavioural reporting.
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 behaviours, 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 behaviour was the only one to yield a prevalence in black MSM (44·1%) similar to that observed (43·4%).
The Eunice Kennedy Shriver National Institute of Child Health and Development, the National Institute of Allergy and Infectious Diseases, the National Institute of Minority Health and Health Disparities, and the National Institute of Mental Health.
In the USA, men who have sex men (MSM) are at high risk for HIV, and black MSM have a substantially higher prevalence of infection than white MSM. We created a simulation model to assess the strength of existing hypotheses and data that account for these disparities.