Sexual mixing by HIV status and pre-exposure prophylaxis use among men who have sex with men: addressing information bias

• Type of Material: Article
• Authors: Kevin Maloney, Emory University; David Benkeser, Emory University; Patrick S Sullivan, Emory University; Colleen Kelley, Emory University; Travis Sanchez, Emory University; Samuel M. Jenness, Emory University
• Language: English
• Date: 2022-07-27
• Publisher: Wolters Kluwer Health, Inc.
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2022 Wolters Kluwer Health, Inc. All rights reserved.
• Final Published Version (URL): https://doi.org/10.1097/EDE.0000000000001525
• Title of Journal or Parent Work: Epidemiology
• Volume: 33
• Issue: 6
• Start Page: 808
• End Page: 816
• Grant/Funding Information: This work was supported by grants R21 MH112449, R01 AI138783, and P30 AI050409 (Emory University Center for AIDS Research) from the National Institutes of Health.
• Keywords: systematic bias; statistical models; sexual networks; measurement error; HIV; men who have sex with men
• Research Categories: Health Sciences, Public Health; Health Sciences, Epidemiology

Abstract

Background: Population-level estimates of sexual network mixing for parameterizing prediction models of pre-exposure prophylaxis (PrEP) effectiveness are needed to inform prevention of HIV transmission among men who have sex with men (MSM). Estimates obtained by egocentric sampling are vulnerable to information bias due to incomplete respondent knowledge. Methods: We estimated patterns of serosorting and PrEP sorting among MSM in the United States using data from a 2017–2019 egocentric sexual network study. Respondents served as proxies to report the HIV status and PrEP use of recent sexual partners. We contrasted results from a complete-case analysis (unknown HIV and PrEP excluded) versus a bias analysis with respondent-reported data stochastically reclassified to simulate unobserved self-reported data from sexual partners. Results: We found strong evidence of preferential partnering across analytical approaches. The bias analysis showed concordance between sexual partners of HIV diagnosis and PrEP use statuses for MSM with diagnosed HIV (39%; 95% simulation interval: 31, 46), MSM who used PrEP (32%; 21, 37), and MSM who did not use PrEP (83%; 79, 87). The fraction of partners with diagnosed HIV was higher among MSM who used PrEP (11%; 9, 14) compared to MSM who did not use PrEP (4%; 3, 5). Comparatively, across all strata of respondents, the complete-case analysis overestimated the fractions of partners with diagnosed HIV or PrEP use. Conclusion: We found evidence consistent with HIV and PrEP sorting among MSM, which may decrease the population-level effectiveness of PrEP. Bias analyses can improve mixing estimates for parameterization of transmission models.