Leveraging social networks for identification of people with HIV who are virally unsuppressed.

Autor:	Cummins B; Department of Mathematical Sciences, Montana State University, Bozeman, MT., Johnson K; Department of Mathematical Sciences, Montana State University, Bozeman, MT., Schneider JA; Department of Medicine, University of Chicago.; Department of Public Health Sciences, University of Chicago, Chicago, IL., Del Vecchio N; Department of Public Health Sciences, University of Chicago, Chicago, IL., Moshiri N; Computer Science and Engineering Department., Wertheim JO; Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California, San Diego, La Jolla, CA, USA., Goyal R; Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California, San Diego, La Jolla, CA, USA., Skaathun B; Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California, San Diego, La Jolla, CA, USA.
Jazyk:	angličtina
Zdroj:	AIDS (London, England) [AIDS] 2024 Feb 01; Vol. 38 (2), pp. 245-254. Date of Electronic Publication: 2023 Oct 26.
DOI:	10.1097/QAD.0000000000003767
Abstrakt:	Objectives: This study investigates primary peer-referral engagement (PRE) strategies to assess which strategy results in engaging higher numbers of people with HIV (PWH) who are virally unsuppressed. Design: We develop a modeling study that simulates an HIV epidemic (transmission, disease progression, and viral evolution) over 6 years using an agent-based model followed by simulating PRE strategies. We investigate two PRE strategies where referrals are based on social network strategies (SNS) or sexual partner contact tracing (SPCT). Methods: We parameterize, calibrate, and validate our study using data from Chicago on Black sexual minority men to assess these strategies for a population with high incidence and prevalence of HIV. For each strategy, we calculate the number of PWH recruited who are undiagnosed or out-of-care (OoC) and the number of direct or indirect transmissions. Results: SNS and SPCT identified 256.5 [95% confidence interval (CI) 234-279] and 15 (95% CI 7-27) PWH, respectively. Of these, SNS identified 159 (95% CI 142-177) PWH OoC and 32 (95% CI 21-43) PWH undiagnosed compared with 9 (95% CI 3-18) and 2 (95% CI 0-5) for SPCT. SNS identified 15.5 (95% CI 6-25) and 7.5 (95% CI 2-11) indirect and direct transmission pairs, whereas SPCT identified 6 (95% CI 0-8) and 5 (95% CI 0-8), respectively. Conclusion: With no testing constraints, SNS is the more effective strategy to identify undiagnosed and OoC PWH. Neither strategy is successful at identifying sufficient indirect or direct transmission pairs to investigate transmission networks. (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)
Databáze:	MEDLINE
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