Intersection of Syphilis and Human Immunodeficiency Virus (HIV) Networks to Identify Opportunities to Enhance HIV Prevention

Background Human immunodeficiency virus (HIV) and syphilis infection continue at disproportionate rates among minority men who have sex with men (MSM) in the United States. The integration of HIV genetic clustering with partner services can provide important insight into local epidemic trends to guide interventions and control efforts. Methods We evaluated contact networks of index persons defined as minority men and transgender women diagnosed with early syphilis and/or HIV infection between 2018 and 2020 in 2 North Carolina regions. HIV clusters were constructed from pol sequences collected through statewide surveillance. A combined "HIV-risk" network, which included persons with any links (genetic or sexual contact) to HIV-positive persons, was evaluated by component size, demographic factors, and HIV viral suppression. Results In total, 1289 index persons were identified and 55% named 1153 contacts. Most index persons were Black (88%) and young (median age 30 years); 70% had early syphilis and 43% had prevalent HIV infection. Most people with HIV (65%) appeared in an HIV cluster. The combined HIV-risk network (1590 contact network and 1500 cluster members) included 287 distinct components; however, 1586 (51%) were in a single component. Fifty-five percent of network members with HIV had no evidence of viral suppression. Overall, fewer index persons needed to be interviewed to identify 1 HIV-positive member without viral suppression (1.3 vs 4.0 for contact tracing). Conclusions Integration of HIV clusters and viral loads illuminate networks with high HIV prevalence, indicating recent and ongoing transmission. Interventions intensified toward these networks may efficiently reach persons for HIV prevention and care re-engagement. HIV risk networks with high viremia were identified among 1289 minority men and transgender women diagnosed with early syphilis or new HIV infection. Combined contact and HIV molecular networks can be leveraged to identify subgroups for intensified care and prevention.