Bayesian estimation of MSM population size in C?te d’Ivoire

Abstract C?te d’Ivoire has one of the largest HIV epidemics in West Africa with around half million people living with HIV. Key populations like gay men and other men who have sex with men (MSM) are often disproportionately burdened with HIV due to specific acquisition and transmission risks. Quantifying the MSM population sizes at subnational level is critical to improving the HIV prevention interventions. While survey-based direct estimates of MSM numbers are available at a few urban centers in C?ote d’Ivoire, no data on MSM population size exists at other areas without any community infrastructure to facilitate sufficient access to the MSM community. We use this limited data in a Bayesian regression setup to produce first empirically calculated estimates of the numbers of MSM in all areas of C?ote d’Ivoire prioritized in the HIV response. Our hierarchical model imputes missing covariates using geospatial information and allows for proper uncertainty quantification leading to meaningful confidence bounds for the predicted MSM population size estimates. The intended impact of this process is to increase uptake and use of high quality, comprehensive epidemiologic and interventional data in program planning. These estimates will help design future surveys and support the planning of the scale and content of HIV prevention and treatment programs for MSM in C?ote d’Ivoire.