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Background Identifying areas of high background HIV diagnosis rates (bHIV) is critical for future PrEP trials using counterfactual study designs to estimate efficacy and to facilitate effective implementation of HIV prevention interventions. In this study, we used a multiple data source model to estimate bHIV between 2012 and 2019 in people who could benefit from PrEP (PWBP) but are not taking PrEP to identify with greater precision areas of high HIV transmission at the Metropolitan Statistical Area (MSA) level. We compared bHIV in PWBP in PURPOSE2 (NCT04925752) trial sites to those in the DISCOVER trial (NCT02842086) to demonstrate how this approach can inform site selection in future PrEP clinical trials and support delivery of PrEP interventions. Methods Number of new HIV diagnoses, number of individuals with a PrEP indication, and person-time on PrEP or after HIV diagnosis (obtained from published surveillance data) and pharmacy claims data (IQVIA PharMetrics Plus) were used to calculate estimated bHIV in a multivariate Poisson regression model for PWBP in 108 MSAs and across states between 2012 and 2019. Results Overall, bHIV among PWBP decreased from 4.42 per 100 person-years (PY) (95% CI 4.38 – 4.47) in 2012 to 3.14 per 100 PY (95% CI 3.10 – 3.17) in 2019. However, bHIV among PWBP in MSAs with PURPOSE2 trial sites were consistently higher (from 4.69 per 100 PY [95% CI 4.56 – 4.81] in 2012 to 3.58 per 100 PY [95% CI 3.49 – 3.67] in 2019) compared to areas with DISCOVER-only sites (from 3.77 per 100 PY [95% CI 3.53 – 4.01] in 2012 to 2.83 per 100 PY [95% CI 2.63 – 3.03] in 2019; Figure 1A). Within states, we identified specific localities with high bHIV among PWBP, such as in Illinois where state level HIV diagnosis rate was 2.65 per 100 PY [95% CI 2.50 – 2.80] but as high as 6.04 per 100 PY [95% CI 5.67 - 6.40] in the MSA with a PURPOSE2 site (Figure 1B). Figure:Estimated background HIV diagnosis rates (bHIV) in people who could benefit from PrEP by MSAs selected by DISCOVER/PURPOSE2 trials (A) from 2012 to 2019 and (B) in 2019 in the US. Conclusion We found considerable variation in bHIV at the MSA level among PWBP who are not taking PrEP, including a concentration of MSAs in the Southeastern US with high rates of new HIV diagnosis. Our methodology for leveraging existing surveillance data to identify areas of high bHIV with greater precision may provide a valuable approach to support future counterfactual clinical trial designs and prioritize resources for delivery of PrEP services. Disclosures Melanie de Boer, PhD, Gilead Sciences: Employee|Gilead Sciences: Stocks/Bonds Jason Yuan, n/a, Gilead Sciences: Employee|Gilead Sciences: Stocks/Bonds Juan Yang, PhD, Gilead Sciences: Employee|Gilead Sciences: Stocks/Bonds Lillian Brown, MD, PhD, Gilead Sciences: Stocks/Bonds Carlo Hojilla, PhD, Gilead Sciences: Employee|Gilead Sciences: Stocks/Bonds Christoph C. Carter, MD, PhD, Gilead Sciences: Employee|Gilead Sciences: Employee|Gilead Sciences: Stocks/Bonds|Gilead Sciences: Stocks/Bonds Moupali Das, MD, Gilead Sciences: Employee|Gilead Sciences: Employee|Gilead Sciences: Stocks/Bonds|Gilead Sciences: Stocks/Bonds Li Tao, MD, PhD, Gilead Sciences: Employee|Gilead Sciences: Employee|Gilead Sciences: Stocks/Bonds|Gilead Sciences: Stocks/Bonds. |
