Philip A Chan1, Joseph W Hogan, Austin Huang, Allison DeLong, Marco Salemi, Kenneth H Mayer, Rami Kantor. 1. *Division of Infectious Diseases, Department of Medicine, Alpert Medical School of Brown University, Providence, RI; †Center for Statistical Sciences, Brown University School of Public Health, Providence, RI; ‡Department of Pathology, University of Florida, Gainesville, FL; and §Fenway Health, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA.
Abstract
BACKGROUND: Molecular epidemiological evaluation of HIV-1 transmission networks can elucidate behavioral components of transmission that can be targets for intervention. METHODS: We combined phylogenetic and statistical approaches using pol sequences from patients diagnosed between 2004 and 2011 at a large HIV center in Rhode Island, following 75% of the state's HIV population. Phylogenetic trees were constructed using maximum likelihood, and putative transmission clusters were evaluated using latent class analyses to determine association of cluster size with underlying demographic/behavioral characteristics. A logistic growth model was used to assess intracluster dynamics over time and predict "active" clusters that were more likely to harbor undiagnosed infections. RESULTS: Of the 1166 HIV-1 subtype B sequences, 31% were distributed among 114 statistically supported, monophyletic clusters (range: 2-15 sequences/cluster). Sequences from men who have sex with men (MSM) formed 52% of clusters. Latent class analyses demonstrated that sequences from recently diagnosed (2008-2011) MSM with primary HIV infection (PHI) and other sexually transmitted infections (STIs) were more likely to form larger clusters (odds ratio: 1.62-11.25, P < 0.01). MSM in clusters were more likely to have anonymous partners and meet partners at sex clubs and pornographic stores. Four large clusters with 38 sequences (100% male, 89% MSM) had a high probability of harboring undiagnosed infections and included younger MSM with PHI and STIs. CONCLUSIONS: In this first large-scale molecular epidemiological investigation of HIV-1 transmission in New England, sexual networks among recently diagnosed MSM with PHI and concomitant STIs contributed to the ongoing transmission. Characterization of transmission dynamics revealed actively growing clusters, which may be targets for intervention.
BACKGROUND: Molecular epidemiological evaluation of HIV-1 transmission networks can elucidate behavioral components of transmission that can be targets for intervention. METHODS: We combined phylogenetic and statistical approaches using pol sequences from patients diagnosed between 2004 and 2011 at a large HIV center in Rhode Island, following 75% of the state's HIV population. Phylogenetic trees were constructed using maximum likelihood, and putative transmission clusters were evaluated using latent class analyses to determine association of cluster size with underlying demographic/behavioral characteristics. A logistic growth model was used to assess intracluster dynamics over time and predict "active" clusters that were more likely to harbor undiagnosed infections. RESULTS: Of the 1166 HIV-1 subtype B sequences, 31% were distributed among 114 statistically supported, monophyletic clusters (range: 2-15 sequences/cluster). Sequences from men who have sex with men (MSM) formed 52% of clusters. Latent class analyses demonstrated that sequences from recently diagnosed (2008-2011) MSM with primary HIV infection (PHI) and other sexually transmitted infections (STIs) were more likely to form larger clusters (odds ratio: 1.62-11.25, P < 0.01). MSM in clusters were more likely to have anonymous partners and meet partners at sex clubs and pornographic stores. Four large clusters with 38 sequences (100% male, 89% MSM) had a high probability of harboring undiagnosed infections and included younger MSM with PHI and STIs. CONCLUSIONS: In this first large-scale molecular epidemiological investigation of HIV-1 transmission in New England, sexual networks among recently diagnosed MSM with PHI and concomitant STIs contributed to the ongoing transmission. Characterization of transmission dynamics revealed actively growing clusters, which may be targets for intervention.
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