Background. Clinically, human immunodeficiency virus type 1 (HIV-1) pol sequences are used to evaluate for drug resistance. These data can also be used to evaluate transmission networks and help describe factors associated with transmission risk.Methods. HIV-1 pol sequences from participants at 5 sites in the CFAR Network of Integrated Clinical Systems (CNICS) cohort from 2000-2009 were analyzed for genetic relatedness. Only the first available sequence per participant was included. Inferred transmission networks ("clusters") were defined as ≥2 sequences with ≤1.5% genetic distance. Clusters including ≥3 patients ("networks") were evaluated for clinical and demographic associations.Results. Of 3697 sequences, 24% fell into inferred clusters: 155 clusters of 2 individuals ("dyads"), 54 clusters that included 3-14 individuals ("networks"), and 1 large cluster that included 336 individuals across all study sites. In multivariable analyses, factors associated with being in a cluster included not using antiretroviral (ARV) drugs at time of sampling (P < .001), sequence collected after 2004 (P < .001), CD4 cell count >350 cells/mL (P < .01), and viral load 10 000-100 000 copies/mL (P < .001) or >100 000 copies/mL (P < .001). In networks, women were more likely to cluster with other women (P < .001), and African Americans with other African Americans (P < .001).Conclusions. Molecular epidemiology can be applied to study HIV transmission networks in geographically and demographically diverse cohorts. Clustering was associated with lack of ARV use and higher viral load, implying transmission may be interrupted by earlier diagnosis and treatment. Observed female and African American networks reinforce the importance of diagnosis and prevention efforts targeted by sex and race.

Efficient and effective HIV prevention measures for generalized epidemics in sub-Saharan Africa have not yet been validated at the population-level. Design and impact evaluation of such measures requires fine-scale understanding of local HIV transmission dynamics. The novel tools of HIV phylogenetics and molecular epidemiology may elucidate these transmission dynamics. Such methods have been incorporated into studies of concentrated HIV epidemics to identify proximate and determinant traits associated with ongoing transmission. However, applying similar phylogenetic analyses to generalized epidemics, including the design and evaluation of prevention trials, presents additional challenges. Here we review the scope of these methods and present examples of their use in concentrated epidemics in the context of prevention. Next, we describe the current uses for phylogenetics in generalized epidemics, and discuss their promise for elucidating transmission patterns and informing prevention trials. Finally, we review logistic and technical challenges inherent to large-scale molecular epidemiological studies of generalized epidemics, and suggest potential solutions.

The associations of acute HIV infection (AHI) and other predictors with transmitted drug resistance (TDR) prevalence were assessed in a cohort of HIV-infected, antiretroviral-naïve patients. AHI was defined as being seronegative with detectable HIV RNA. Binomial regression was used to estimate prevalence ratios and 95% confidence intervals (CIs) for associations with TDR. Among 43 AHI patients, TDR prevalence was 20.9%, while prevalence was 8.6% among 677 chronically-infected patients. AHI was associated with 1.9 times the prevalence of TDR (95% CI: 1.0, 3.6) in multivariable analysis. AHI patients may represent a vanguard group that portends increasing TDR in the future.

Latinos are more likely to initiate HIV care later in the course of illness than are black and white persons and account for a majority of several ADEs. Strategies to improve earlier HIV testing among Latinos in new settlement areas are needed.

Objectives Despite prevention efforts new HIV diagnoses continue in the Southern US, where the epidemic is characterized by significant racial/ethnic disparities. We integrated phylogenetic analyses with clinical data to reveal trends in local HIV transmission. Design Cross-sectional analysis of 1671 HIV-infected individuals each with one B-subtype pol sequence obtained during chronic (82%; UNC Center for AIDS Research Clinical Cohort) or acute/recent (18%; Duke/UNC Acute HIV Consortium) infection. Methods Phylogenies were inferred using neighbor joining to select related sequences then confirmed with Bayesian methods. We characterized transmission clusters (clades n≥3 sequences supported by posterior probabilities=1) by factors including race/ethnicity and transmission risk. Factors associated with cluster membership were evaluated for newly diagnosed patients. Results Overall, 72% were male, 59% black and 39% MSM. A total of 557 (33%) sequences grouped in either 108 pairs (n=216) or 67 clusters (n=341). Clusters ranged from 3–36 (median 4) members. Composition was delineated primarily by race, with 28% exclusively black, and to a lesser extent by risk group. Both MSM and heterosexuals formed discrete clusters though substantial mixing was observed. In multivariable analysis, patients with age ≤30 years (P=0.009), acute infection (P=0.02), local residence (P=0.002), and transmitted drug resistance (P=0.02) were more likely to be cluster members while Latinos were less likely (P<0.001). Conclusions Integration of molecular, clinical and demographic data offers a unique view into the structure of local transmission networks. Clustering by black race, youth and TDR and inability to identify Latino clusters will inform prevention, testing and linkage to care strategies.