Targeting new HIV prevention strategies through the combination of research and public health surveillance dataPublic Deposited
Phylogenetic analysis of HIV is a useful tool in determining factors that may contribute to transmission cluster growth. To better target HIV prevention, it is necessary to understand how research and surveillance data can be combined in a meaningful way.HIV genetic sequences were collected in the RADAR cohort of YMSM (aged 16-29) from 2015-2017. Sequence data were also obtained from the Chicago Department of Public Health (CDPH) and included those individuals who were within two-degree connections of RADAR participants. Pairwise genetic distances of HIV pol sequences were determined with transmission ties inferred between participants whose viral sequences were ≤1.5% genetically distant. Transmission clusters comprised ≥2 persons. Network analyses were utilized to compare individuals based on demographic characteristics.Overall, 221 (21.4%) RADAR participants were identified as HIV-positive with 150 (67.9%) viral sequences available. We identified 8 transmission clusters with 22 ties between 24 participants. Those in a transmission cluster, compared to those not in a cluster, were significantly younger (p<0.001), more recently diagnosed (p<0.001), and less dependent on marijuana or alcohol (both p<0.001). Combined RADAR and CDPH data yielded 7837 sequences among which existed 11 transmission clusters with 3325 ties between 451 individuals. Ninety-three (62%) RADAR participants clustered with CDPH data. The majority of individuals in the combined data were black (2889, 64.1%) and aged 20-29 (271, 60.1%). Racial homophily was not a significant predictor of ties (p=0.302) while age category homophily was (p<0.001). Fewer than expected RADAR participants clustered with CDPH data suggesting non-clustering individuals are either being diagnosed HIV outside city limits or have unexpectedly divergent sequences. Combining research and surveillance data to construct post hoc transmission networks has the potential to provide novels methods for analyzing data among new HIV infections. Future work should aim to assess survey data in the context of these larger transmission network structures.
- In Collection: