Background: Molecular epidemiology is often the only means to reveal difficult-to-measure patterns of HIV transmission in local epidemics. Of particular interest are “bridge” individuals that link otherwise disconnected network components, evaluated here for the inferred San Diego Primary Infection Cohort (SDPIC) HIV transmission network.
Methods: We inferred a molecular transmission network (MTN) from a curated collection of 1024 partial pol sequences, representing 713 SDPIC participants sampled between 1996 and 2013, and 311 sequences from area chronically infected individuals. Two individuals (nodes) were linked if their sequences were <1.5% distant (TN93 metric). Network degree, mean path length (MPL), and betweenness centrality were computed for each network node, and statistical analyses were used to examine which sociodemographic factors associated with network properties. We also investigated the association of a novel “uniqueness” score with the various measures of network centrality. This score combined the demographic attributes of age, race, ethnicity, HIV risk factor, and location of residence into a single score, which was then used to compare all of the individuals within each transmission cluster relative to one another.
Results: 42.1% of individuals in our study were linked to at least one other individual in the MTN. Age of individuals was the only sociodemographic measure marginally associated with centrality in univariate analyses [p=0.053, age vs clustering, t-test]. In clusters comprising 4 or more individuals, central nodes (low MPL) were significantly more likely [p=0.05, Fishers Exact Test] to have higher uniqueness scores, and the highest scoring individuals had significantly higher betweenness centrality [25.6% vs 8.2%, p=0.041, t-test].
Conclusions: In models of epidemiologic spread, individuals who serve as bridges between otherwise disconnected groups have been implicated as important drivers of HIV epidemics. Our analyses demonstrate in the San Diego HIV epidemic, bridging individuals were sociodemographically unique. Such uniqueness represents a higher degree of disassortative mixing by these key individuals, suggesting that disassortative partnerships may disproportionately drive HIV epidemics.