Project Details
Description
PROJECT SUMMARY Sub-Saharan Africa (SSA) is disproportionately impacted by the HIV epidemic, with ongoing substantial HIV transmission despite large reductions in new HIV infections. Despite clear evidence at the couple-level that HIV test-and-treat strategies are successful at reducing HIV transmission, population-level trials have shown mixed effectiveness of test-and-treat strategies to reduce HIV incidence. There is evidence of disparities in testing and treatment engagement, particularly among marginalized populations. Furthermore, these disparities are frequently along the same characteristics as sexual network clustering. Therefore, a potential explanation for a smaller than expected incidence impact is sexual network clustering, partnering of like-with-like, by HIV testing and treatment. Indeed, my preliminary work showed that couples in South Africa who reported never testing for HIV were nearly 2 times more likely (1.9, 95% CI=1.8-2.0) to be partnered with one another than expected by random chance. But this finding needs replication, as there is little empirical evidence to support these claims. Through network analyses and simulations, contextualized with community interviews, this career development award will assess whether sexual network clustering impacts the effectiveness of HIV treatment as prevention. These results will inform population-level treatment targets. Further, they will allow me to test the utility of network-driven strategies to drive testing and treatment and provide clear guidance to maximize the impact of these interventions. Research aims will include: 1) Identify the network context of HIV test-and-treat interventions in SSA by (A.) Characterizing the sexual network position of people engaged in test-and-treat, and (B.) Estimating the level of sexual network clustering by test-and-treat; 2) Evaluate the impact of network- driven strategies of HIV interventions using network models parametrized with data on engagement in HIV test-and-treat and sexual network context; 3) Translate modeling and network analyses to real-world settings. This proposal will leverage previously collected data from Uganda, Malawi, and Nigeria: the Rakai Community Cohort Study, the TRUST/RV368 Study, Population-based HIV Impact Assessments, and the Likoma Network Study, and collect original qualitative data in Rakai, Uganda. These sources include data on both “general populations” and “key populations,” specifically fisherfolk and men who have sex with men and transgender women, at increased risk of HIV infection. This work will build on my existing global collaborations, while developing my expertise in network science and translation through a mentorship team with extensive experience in network data collection and conducting community-informed work. Building on these findings, future funding will be sought to collect expanded sexual network data and develop network-level intervention strategies. My training plan will include gaining experience in participatory modeling and qualitative work, a novel skillset among network modelers. This career development project will provide me with expertise to begin an independent career as a leader in HIV and sexual network research.
Status | Active |
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Effective start/end date | 7/16/24 → 6/30/28 |
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