Integrating Partner Services and Molecular Epidemiology Data to Enhance HIV Transmission Disruption in Rhode Island

Evaluate added value of integrating partner services and molecular epidemiology data to disrupt HIV transmission.

Integration of statewide partner services and molecular databases.

We evaluated overlap of persons and their social/molecular links in contact tracing (Contact Tracing Database [CTDB], 2008-2022) and HIV-1 genomic (Genomic Database [GDB], 2004-2023) databases using Jaccard coefficient (JC); inferred molecular clustering using phylogeny; assessed care engagement gaps by developing a "partner naming" cascade; and explored associations of molecular clustering and partner naming using generalized estimating equations.

Among 2418 CTDB and 2527 GDB individuals, 894 (JC = 0.22) and 59 links (JC = 0.012) appeared in both databases, demonstrating low overlap. Molecular clustering occurred in 48% of all GDB persons, 65% of persons in both databases, 71% of persons providing partner data, and 88% of named partners in both databases. Of 1342 named partners, contacts were attempted for 66%, and 93% were reached; of those reached, 71% were newly HIV-tested, of whom 27% were newly diagnosed, and all newly diagnosed were sequenced. Men who have sex with men and people who inject drugs were more likely to cluster molecularly in the GDB if linked in the CTDB, while high-risk heterosexuals were less likely. Men who have sex with men and older individuals were more likely to be linked in the CTDB if they clustered molecularly, while people who inject drugs were less likely.

Comprehensive, statewide integration of contact tracing and molecular data enables public health insights not available with one source alone, underscoring the added value of data integration in identifying gaps to improve HIV prevention services.