Background: Understanding the dynamics of HIV transmission may provide opportunities for public health interventions. Methodology: We inferred a partial local transmission network among 478 recently HIV infected persons and 170 of their HIV infected sexual and social contacts in San Diego, California (n=648) using HIV pol sequences collected from 1996 to 2011. We linked two individuals (nodes) in the network whenever their pol sequences were less than 1.5% distant (Tamura Nei 1993 distance). Whenever possible, we assigned a direction to the network edge, based on the duration of infection for each partner. Using only baseline data after 2004, when network sampling was sufficiently dense (n=157), we defined a transmission network score (TNS) to estimate the risk of HIV transmission from a newly diagnosed individual to a new partner and potential impact of prevention interventions. TNS is a function of the total degree of the node at baseline (set to 0 if no connections are inferred), conditioned on the network inferred at the time of each subject’s baseline sequence. Results: HIV-1 pol sequences from 339 of 648 individuals (52.3%) were linked to sequences from at least one other participant (i.e., clustered). The top quintile of the TNS distribution was designated as ‘high’ (TNS > 0.75, n=33) and all others as ‘low’ (n=124). Future transmission risk was characterized by identification of a new outbound connection within 1 year of enrollment. High TNS was significantly correlated with baseline risk behaviors (number of unique sexual partners and insertive unprotected anal intercourse [p=0.014 and 0.0455, respectively]). Baseline viral load (VL) and high TNS were not significantly correlated in univariate analysis (p = 0.27), but in a multivariable analysis, both VL and high TNS at baseline were independently correlated with predicted risk of HIV transmission within the first year after presentation (p=0.0164 and p=0.0018, respectively). Retrospective analysis of antiretroviral therapy (ART) use, and simulations of ART targeted to individuals with the highest TNS, suggested significantly reduced network level HIV transmission (p<0.05). Conclusions: Sequence data from an HIV screening program focused on recently infected persons and their social and sexual contacts enabled the characterization of a highly connected transmission network. When TNS was incorporated into a multivariate model with VL, the prediction of transmission risk significantly improved, suggesting that VL and TNS are informed by independent transmission risk factors. The network-based TNS was significantly 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 transmitting HIV.
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