Age bias in survey sampling and implications for estimating HIV prevalence in men who have sex with men: insights from mathematical modelling

Authored by L F Johnson, P Mulongeni, A Marr, T Lane

Date Published: 2018

DOI: 10.1017/s0950268818000961

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative Flow charts Mathematical description

Model Code URLs: Model code not found

Abstract

Respondent-driven sampling (RDS) is widely used to estimate HIV prevalence in men who have sex with men (MSM). Mathematical models that are calibrated to these data may be compromised if they tail to account for selection biases in RDS surveys. To quantify the potential extent of this bias, an agent-based model of HIV in South Africa was calibrated to HIV prevalence and sexual behaviour data from South African studies of MSM, first reweighting the modelled MSM population to match the younger age profile of the RDS surveys (age-adjusted analysis) and then without reweighting (unadjusted analysis). The model estimated a median HIV prevalence in South African MSM in 2015 of 34.6\% (inter-quartile range (IQR): 31,4-37.2\%) in the age-adjusted analysis, compared with 26.1\% (IQR: 24.1-28.4\%) in the unadjusted analysis. The median lifetime risk of acquiring HIV in exclusively homosexual men was 88\% (IQR: 82-92\%) in the age-adjusted analysis, compared with 76\% (IQR: 64-85\%) in the unadjusted analysis. These results suggest that RDS studies may under-estimate the exceptionally high HIV prevalence rates in South African MSM because of over-sampling of younger MSM. Mathematical models that are calibrated to these data need to control for likely over-sampling of younger MSM.

Tags

mathematical modelling Epidemiology Infection Risk population men who have sex with men transmission Impact South-africa Workers Homosexual-men Hiv incidence South africa Recruitment patterns