Using HIV Networks to Inform Real Time Prevention Interventions

• Published in: PloS one Vol. 9; no. 6; p. e98443
• Main Authors: Little, Susan J., Kosakovsky Pond, Sergei L., Anderson, Christy M., Young, Jason A., Wertheim, Joel O., Mehta, Sanjay R., May, Susanne, Smith, Davey M.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 05.06.2014; Public Library of Science (PLoS)
• Subjects: Adult; Analysis; Antiretroviral agents; Antiretroviral drugs; Antiretroviral therapy; Biology and Life Sciences; California; Cluster Analysis; Data processing; Disease transmission; Drug resistance; Epidemics; Female; Health risks; HIV; HIV Infections - diagnosis; HIV Infections - prevention & control; HIV Infections - transmission; HIV tests; HIV-1 - genetics; Human immunodeficiency virus; Humans; Male; Mass Screening; Medicine and health sciences; Middle Aged; pol Gene Products, Human Immunodeficiency Virus - genetics; Population Surveillance; Prevention; Risk; Risk taking; Sequence Analysis, DNA; Sexual Behavior; Sexual Partners; Sexually transmitted diseases; STD; Target recognition; Young Adult; California; La Jolla California; United States > US
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0098443

To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission. HIV-1 pol sequence data were analyzed to infer the local transmission network. We analyzed HIV-1 pol sequence data to infer a partial local transmission network among 478 recently HIV-1 infected persons and 170 of their sexual and social contacts in San Diego, California. A transmission network score (TNS) was developed to estimate the risk of HIV transmission from a newly diagnosed individual to a new partner and target prevention interventions. HIV-1 pol sequences from 339 individuals (52.3%) were highly similar to sequences from at least one other participant (i.e., clustered). A high TNS (top 25%) was significantly correlated with baseline risk behaviors (number of unique sexual partners and insertive unprotected anal intercourse (p = 0.014 and p = 0.0455, respectively) and predicted risk of transmission (p<0.0001). Retrospective analysis of antiretroviral therapy (ART) use, and simulations of ART targeted to individuals with the highest TNS, showed significantly reduced network level HIV transmission (p<0.05). Sequence data from an HIV-1 screening program focused on recently infected persons and their social and sexual contacts enabled the characterization of a highly connected transmission network. The network-based risk score (TNS) was highly correlated with transmission risk behaviors and outcomes, and can be used identify and target effective prevention interventions, like ART, to those at a greater risk for HIV-1 transmission.