Leveraging Networks, Epidemiology, and Epidemic Modeling: Creative Approaches for HIV Elimination

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Abstract New HIV infections in the U.S. are beginning to decline, but marginalized groups such as substance using populations continue to experience new infections. Individuals with acute and early HIV (AEH) and those who are HIV infected, but out of care, are key drivers of ongoing transmission. Biological interventions such as pre-exposure prophylaxis (PrEP) that reduces HIV acquisition by >90% can curtail transmission, but marginalized groups have low utilization rates. Social network factors have been noted as contributing to the difference in rates of HIV acquisition. Public health departments traditionally used contact tracing (asking newly HIV diagnosed clients to identify their sex or drug contacts) to identify individuals who are unaware of their HIV infection, but this information is often incomplete due to underreporting. Experts are now turning toward molecular network data (individuals linked by similar HIV-1 pol sequences) in conjunction with contact tracing information for HIV epidemic response. While informative, sampling challenges limit the reliance on these sources alone for making inferences about HIV transmission. Social network data, in contrast, are more complete than sexual contact data and often include substance use and sexual partners in networks. Despite indication of the benefits of combining these data, little research has been conducted on how they can be integrated for HIV prevention and care. The overall goal of this project is to better understand the complex and overlapping social and molecular network dynamics involved in HIV transmission in order to more effectively prioritize interventions to reduce HIV incidence.