HIV Transmission Cluster Analysis to Inform Prevention
Location(s): United States
Men who have sex with men (MSM) are disproportionately affected by the HIV/AIDS epidemic. They are often referred to collectively as a high-risk group, but this generalization belies the fact that there is a high degree of heterogeneity of HIV risk within the population. Certain socio-ecological factors place some MSM at higher risk for HIV. There are a number of potential drivers of the HIV epidemic, including substance use, undiagnosed infections and high number of sexual partners. However, these broad categories need refinement in order to identify transmission patterns, as it remains unclear which drivers are contributing to the epidemic with HIV transmission as the biological outcome. Real-time identification of epidemiological hot spots, pinpointing the chains of viral transmission and biologically linking drivers of the epidemic are needed to effectively target prevention strategies and interrupt these chains of HIV transmission. Increasing use of antiretroviral (ARV) resistance testing in response to revised clinical guidelines has enriched the availability of viral sequences to study HIV transmission epidemiology. DNA sequencing can be used to establish epidemiological linkages between infected persons. Such linkages are referred to as HIV transmission clusters, comprised of cases whose viruses share sufficient phylogenetic similarities to suggest a recent common source of infection or participation in linked chains of transmission. Identifying clusters that account for the largest proportion of onward transmissions and characterizing the structural, behavioral and biological correlates that predict transmissibility would inform the development of targeted interventions. The proposed study will use a combination of biological, epidemiological, behavioral and psychosocial research tools to obtain an innovative perspective on the HIV epidemic among MSM. The specific aims are: 1) to characterize HIV transmission clusters and correlates associated with transmission; 2) to evaluate the relative impact of acute, recent and long-term HIV infections on transmission clusters; and 3) to assess HIV transmission cluster patterns in relation to attempted risk reduction strategies. We are poised to analyze viral sequences to elucidate the key patterns of HIV transmission. We will enhance the utility of existing data by creating a population-based, analytical database that will harmonize an urban area's HIV/AIDS case registry with viral resistance and sexually transmitted diseases databases. Qualitative interviews will be conducted to describe the psychosocial and behavioral contexts at the level of the transmission cluster to complement the phylogenetic data. Using an adapted Social Ecological model as a conceptual framework, the interviews will elicit seroconversion narratives and obtain detailed data on any specific strategies attempted to prevent HIV transmission. Real-time analysis of HIV transmission cluster data will place us on the leading edge of the epidemic and enable assessment of how high-risk clusters and current prevention strategies affect transmission patterns. The continuing transmission of HIV among MSM calls for maximizing the use of the rich bio-epidemiological data on hand. The proposed HIV transmission cluster analysis will integrate laboratory data with behavioral data to follow key transmission patterns in order to inform tailored development of interventions to interrupt the chains of transmission.