Sexual Mixing by HIV Status and Pre-exposure Prophylaxis Use Among Men Who Have Sex With Men: Addressing Information Bias.
Journal
Epidemiology (Cambridge, Mass.)
ISSN: 1531-5487
Titre abrégé: Epidemiology
Pays: United States
ID NLM: 9009644
Informations de publication
Date de publication:
01 11 2022
01 11 2022
Historique:
pubmed:
28
7
2022
medline:
14
10
2022
entrez:
27
7
2022
Statut:
ppublish
Résumé
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. 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. 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 with 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. 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.
Sections du résumé
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 with 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.
CONCLUSIONS
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.
Identifiants
pubmed: 35895578
doi: 10.1097/EDE.0000000000001525
pii: 00001648-202211000-00006
pmc: PMC9561018
mid: NIHMS1822982
doi:
Substances chimiques
Anti-HIV Agents
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
808-816Subventions
Organisme : NIAID NIH HHS
ID : P30 AI050409
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI138783
Pays : United States
Organisme : NIMH NIH HHS
ID : R21 MH112449
Pays : United States
Informations de copyright
Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.
Déclaration de conflit d'intérêts
The authors report no conflicts of interest.
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