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Identification of Genetically Related HCV Infections Among Self-Described Injecting Partnerships.
Tully, Damien C; Hahn, Judith A; Bean, David J; Evans, Jennifer L; Morris, Meghan D; Page, Kimberly; Allen, Todd M.
Affiliation
  • Tully DC; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Hahn JA; Center for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Bean DJ; Department of Medicine, University of California, San Francisco, California, USA.
  • Evans JL; Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts, USA.
  • Morris MD; Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA.
  • Page K; Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA.
  • Allen TM; Department of Internal Medicine, University of New Mexico Health Center, Albuquerque, New Mexico, USA.
Clin Infect Dis ; 74(6): 993-1003, 2022 03 23.
Article in En | MEDLINE | ID: mdl-34448809
BACKGROUND: The current opioid epidemic across the United States has fueled a surge in the rate of new hepatitis C virus (HCV) infections among young persons who inject drugs (PWIDs). Paramount to interrupting transmission is targeting these high-risk populations and understanding the underlying network structures facilitating transmission within these communities. METHODS: Deep sequencing data were obtained for 52 participants from 32 injecting partnerships enrolled in the U-Find-Out (UFO) Partner Study, which is a prospective study of self-described injecting dyad partnerships from a large community-based study of HCV infection in young adult PWIDs from San Francisco. Phylogenetically linked transmission events were identified using traditional genetic-distance measures and viral deep sequence phylogenies reconstructed to determine the statistical support of inferences and the direction of transmission within partnerships. RESULTS: Using deep sequencing data, we found that 12 of 32 partnerships were genetically similar and clustered. Three additional phylogenetic clusters were found describing novel putative transmission links outside of the injecting relationship. Transmission direction was inferred correctly for 5 partnerships with the incorrect transmission direction inferred in more than 50% of cases. Notably, we observed that phylogenetic linkage was most often associated with a lower number of network partners and involvement in a sexual relationship. CONCLUSIONS: Deep sequencing of HCV among self-described injecting partnerships demonstrates that the majority of transmission events originate from outside of the injecting partnership. Furthermore, these findings caution that phylogenetic methods may be unable to routinely infer the direction of transmission among PWIDs especially when transmission events occur in rapid succession within high-risk networks.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: HIV Infections / Substance Abuse, Intravenous / Hepatitis C / Drug Users Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Adult / Humans Language: En Journal: Clin Infect Dis Journal subject: DOENCAS TRANSMISSIVEIS Year: 2022 Type: Article Affiliation country: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: HIV Infections / Substance Abuse, Intravenous / Hepatitis C / Drug Users Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Adult / Humans Language: En Journal: Clin Infect Dis Journal subject: DOENCAS TRANSMISSIVEIS Year: 2022 Type: Article Affiliation country: United kingdom