Literature DB >> 34157853

Characterization of HIV Risk Behaviors and Clusters Using HIV-Transmission Cluster Engine Among a Cohort of Persons Living with HIV in Washington, DC.

Brittany Wilbourn1, Brittani Saafir-Callaway2, Kamwing Jair1, Joel O Wertheim3, Oliver Laeyendeker4,5, Jeanne A Jordan1, Michael Kharfen2, Amanda Castel1.   

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.

Entities:  

Keywords:  District of Columbia; HIV; HIV clusters; HIV-TRACE; molecular epidemiology

Mesh:

Year:  2021        PMID: 34157853      PMCID: PMC8501467          DOI: 10.1089/AID.2021.0031

Source DB:  PubMed          Journal:  AIDS Res Hum Retroviruses        ISSN: 0889-2229            Impact factor:   1.723


  35 in total

1.  Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

Authors:  Paul A Harris; Robert Taylor; Robert Thielke; Jonathon Payne; Nathaniel Gonzalez; Jose G Conde
Journal:  J Biomed Inform       Date:  2008-09-30       Impact factor: 6.317

2.  Short Communication: HIV-1 Transmission Networks Across South Korea.

Authors:  Mi Young Ahn; Joel O Wertheim; Woo Joo Kim; Shin-Woo Kim; Jin Soo Lee; Hea Won Ann; Yongduk Jeon; Jin Young Ahn; Je Eun Song; Dong Hyun Oh; Yong Chan Kim; Eun Jin Kim; In Young Jung; Moo Hyun Kim; Wooyoung Jeong; Su Jin Jeong; Nam Su Ku; June Myung Kim; Davey M Smith; Jun Yong Choi
Journal:  AIDS Res Hum Retroviruses       Date:  2017-03-27       Impact factor: 2.205

Review 3.  Connecting the dots: network data and models in HIV epidemiology.

Authors:  Wim Delva; Gabriel E Leventhal; Stéphane Helleringer
Journal:  AIDS       Date:  2016-08-24       Impact factor: 4.177

4.  Development of a large urban longitudinal HIV clinical cohort using a web-based platform to merge electronically and manually abstracted data from disparate medical record systems: technical challenges and innovative solutions.

Authors:  Alan E Greenberg; Harlen Hays; Amanda D Castel; Thilakavathy Subramanian; Lindsey Powers Happ; Maria Jaurretche; Jeff Binkley; Mariah M Kalmin; Kathy Wood; Rachel Hart
Journal:  J Am Med Inform Assoc       Date:  2015-12-31       Impact factor: 4.497

5.  HIV transmission risk behavior among men and women living with HIV in 4 cities in the United States.

Authors:  Lance S Weinhardt; Jeffrey A Kelly; Michael J Brondino; Mary Jane Rotheram-Borus; Sheri B Kirshenbaum; Margaret A Chesney; Robert H Remien; Stephen F Morin; Marguerita Lightfoot; Anke A Ehrhardt; Mallory O Johnson; Sheryl L Catz; Steven D Pinkerton; Eric G Benotsch; Daniel Hong; Cheryl Gore-Felton
Journal:  J Acquir Immune Defic Syndr       Date:  2004-08-15       Impact factor: 3.731

Review 6.  Phylogenetic studies of transmission dynamics in generalized HIV epidemics: an essential tool where the burden is greatest?

Authors:  Ann M Dennis; Joshua T Herbeck; Andrew L Brown; Paul Kellam; Tulio de Oliveira; Deenan Pillay; Christophe Fraser; Myron S Cohen
Journal:  J Acquir Immune Defic Syndr       Date:  2014-10-01       Impact factor: 3.731

7.  Molecular analysis allows inference into HIV transmission among young men who have sex with men in the United States.

Authors:  Y Omar Whiteside; Ruiguang Song; Joel O Wertheim; Alexandra M Oster
Journal:  AIDS       Date:  2015-11-28       Impact factor: 4.177

8.  Using HIV networks to inform real time prevention interventions.

Authors:  Susan J Little; Sergei L Kosakovsky Pond; Christy M Anderson; Jason A Young; Joel O Wertheim; Sanjay R Mehta; Susanne May; Davey M Smith
Journal:  PLoS One       Date:  2014-06-05       Impact factor: 3.240

9.  Social and Genetic Networks of HIV-1 Transmission in New York City.

Authors:  Joel O Wertheim; Sergei L Kosakovsky Pond; Lisa A Forgione; Sanjay R Mehta; Ben Murrell; Sharmila Shah; Davey M Smith; Konrad Scheffler; Lucia V Torian
Journal:  PLoS Pathog       Date:  2017-01-09       Impact factor: 6.823

10.  Defining Care Patterns and Outcomes Among Persons Living with HIV in Washington, DC: Linkage of Clinical Cohort and Surveillance Data.

Authors:  Amanda D Castel; Arpi Terzian; Jenevieve Opoku; Lindsey Powers Happ; Naji Younes; Michael Kharfen; Alan Greenberg
Journal:  JMIR Public Health Surveill       Date:  2018-03-16
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