Bayesian Estimation of MSM Population Size in Côte d’Ivoire

Abhirup Datta, Wenyi Lin, Amrita Rao, Daouda Diouf, Abo Kouame, Jessie K. Edwards, Le Bao, Thomas A. Louis, Stefan Baral

Research output: Contribution to journalArticle

Abstract

Côte d’Ivoire has among the most generalized HIV epidemics in West Africa with an estimated half million people living with HIV. Across West Africa, key populations, including 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 population sizes of MSM at the subnational level is critical to ensuring evidence-based decisions regarding the scale and content of HIV prevention interventions. While survey-based direct estimates of MSM numbers are available in a few urban centers across Côte d’Ivoire, no data on MSM population size exists in other areas without any community group infrastructure to facilitate sufficient access to communities of MSM. The data are used in a Bayesian regression setup to produce estimates of the numbers of MSM in areas of Côte d’Ivoire prioritized in the HIV response. Our hierarchical model imputes missing covariates using geo-spatial information and allows for proper uncertainty quantification leading to confidence bounds for predicted MSM population size estimates. This process provided population size estimates where there are no empirical data, to guide the prioritization of further collection of empirical data on MSM and inform evidence-based scaling of HIV prevention and treatment programs for MSM across Côte d’Ivoire.

Original languageEnglish (US)
Pages (from-to)1-13
Number of pages13
JournalStatistics and Public Policy
Volume6
Issue number1
DOIs
StatePublished - Jan 1 2019

Keywords

  • AIDS
  • Bayesian model
  • Côte d’Ivoire
  • HIV
  • MSM population
  • Small area estimation

ASJC Scopus subject areas

  • Public Administration
  • Statistics and Probability
  • Applied Mathematics
  • Statistics, Probability and Uncertainty

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