Characterization of HIV Risk Behaviors and Clusters Using HIV-Transmission Cluster Engine Among a Cohort of Persons Living with HIV in Washington, DC
Publication: AIDS Research and Human Retroviruses
Volume 37, Issue Number 9
Abstract
Molecular epidemiology (ME) is one tool used to end the HIV epidemic in the United States. We combined clinical and behavioral data with HIV sequence data to identify any overlap in clusters generated from different sequence datasets; to characterize HIV transmission clusters; and to identify correlates of clustering among people living with HIV (PLWH) in Washington, District of Columbia (DC). First, Sanger sequences from DC Cohort participants, a longitudinal HIV study, were combined with next-generation sequences (NGS) from participants in a ME substudy to identify clusters. Next, demographic and self-reported behavioral data from ME substudy participants were used to identify risks of secondary transmission. Finally, we combined NGS from ME substudy participants with Sanger sequences in the DC Molecular HIV Surveillance database to identify clusters. Cluster analyses used HIV-Transmission Cluster Engine to identify linked pairs of sequences (defined as distance ≤1.5%). Twenty-eight clusters of ≥3 sequences (size range: 3–12) representing 108 (3%) participants were identified. None of the five largest clusters (size range: 5–12) included newly diagnosed PLWH. Thirty-four percent of ME substudy participants (n = 213) reported condomless sex during their last sexual encounter and 14% reported a Syphilis diagnosis in the past year. Seven transmission clusters (size range: 2–19) were identified in the final analysis, each containing at least one ME substudy participant. Substudy participants in clusters from the third analysis were present in clusters from the first analysis. Combining HIV sequence, clinical and behavioral data provided insights into HIV transmission that may not be identified using traditional epidemiological methods alone. Specifically, the sexual risk behaviors and STI diagnoses reported in the substudy survey may not have been disclosed during Partner Services activities and the survey data complemented clinical data to fully characterize transmission clusters. These findings can be used to enhance local efforts to interrupt transmission and avert new infections.
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Information & Authors
Information
Published In
AIDS Research and Human Retroviruses
Volume 37 • Issue Number 9 • September 2021
Pages: 706 - 715
PubMed: 34157853
Copyright
Copyright 2021, Mary Ann Liebert, Inc., publishers.
History
Published online: 3 September 2021
Published in print: September 2021
Published ahead of print: 22 July 2021
Published ahead of production: 22 June 2021
Authors
Authors' Contributions
B.W., B.S.-C., K.J., J.O.W., O.L., J.A.J., M.K., and A.C. took part in the writing, reviewing, and revising of the article and also assumes responsibility and accountability for the results.
Author Disclosure Statement
No competing financial interests exist.
Funding Information
This study was supported by the DC Cohort Study (U01 AI69503-03S2; 1R24AI152598-01), a supplement from the Women's Interagency Study for HIV (410722_GR410708), a DC CFAR pilot award, an NIH-NIAID R01 (AI135992), and a 2015 HIV Phylodynamics Supplement award from the DC CFAR, an NIH funded program (AI117970), which is supported by the following NIH Co-Funding and Participating Institutes and Centers: NIAID, NCI, NICHD, NHLBI, NIDA, NIMH, NIA, FIC, NIGMS, NIDDK and OAR. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
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