Impact of COVID-19 Response on the HIV Epidemic in Men Who Have Sex With Men in San Francisco County: The Importance of Rapid Return to Normalcy.

BACKGROUND: In response to the COVID-19 pandemic, San Francisco County (SFC) had to shift many nonemergency health care resources to COVID-19, reducing HIV control resources. We sought to quantify COVID-19 effects on HIV burden among men who have sex with men (MSM) as SFC returns to pre-COVID service levels and progresses toward the Ending the HIV Epidemic (EHE) goals. SETTING: Microsimulation model of MSM in SFC tracking HIV progression and treatment. METHODS: Scenario analysis where services affected by COVID-19 [testing, care engagement, pre-exposure prophylaxis (PrEP) uptake, and retention] return to pre-COVID levels by the end of 2022 or 2025, compared against a counterfactual where COVID-19 changes never occurred. We also examined scenarios where resources are prioritized to reach new patients or retain of existing patients from 2023 to 2025 before all services return to pre-COVID levels. RESULTS: The annual number of MSM prescribed PrEP, newly acquired HIV, newly diagnosed, and achieving viral load suppression (VLS) rebound quickly after HIV care returns to pre-COVID levels. However, COVID-19 service disruptions result in measurable reductions in cumulative PrEP use, VLS person-years, incidence, and an increase in deaths over the 2020-2035 period. The burden is statistically significantly larger if these effects end in 2025 instead of 2022. Prioritizing HIV care/prevention initiation over retention results in more person-years of PrEP but less VLS person-years and more deaths, influencing EHE PrEP outcomes. CONCLUSIONS: Earlier HIV care return to pre-COVID levels results in lower cumulative HIV burdens. Resource prioritization decisions may differentially affect different EHE goals.

Using Microsimulation Modeling to Inform EHE Implementation Strategies in Los Angeles County.

BACKGROUND: Pre-exposure prophylaxis (PrEP) is essential to ending HIV. Yet, uptake remains uneven across racial and ethnic groups. We aimed to estimate the impacts of alternative PrEP implementation strategies in Los Angeles County. SETTING: Men who have sex with men, residing in Los Angeles County. METHODS: We developed a microsimulation model of HIV transmission, with inputs from key local stakeholders. With this model, we estimated the 15-year (2021-2035) health and racial and ethnic equity impacts of 3 PrEP implementation strategies involving coverage with 9000 additional PrEP units annually, above the Status-quo coverage level. Strategies included PrEP allocation equally (strategy 1), proportionally to HIV prevalence (strategy 2), and proportionally to HIV diagnosis rates (strategy 3), across racial and ethnic groups. We measured the degree of relative equalities in the distribution of the health impacts using the Gini index (G) which ranges from 0 (perfect equality, with all individuals across all groups receiving equal health benefits) to 1 (total inequality). RESULTS: HIV prevalence was 21.3% in 2021 [Black (BMSM), 31.1%; Latino (LMSM), 18.3%, and White (WMSM), 20.7%] with relatively equal to reasonable distribution across groups (G, 0.28; 95% confidence interval [CI], 0.26 to 0.34). During 2021-2035, cumulative incident infections were highest under Status-quo (n = 24,584) and lowest under strategy 3 (n = 22,080). Status-quo infection risk declined over time among all groups but remained higher in 2035 for BMSM (incidence rate ratio, 4.76; 95% CI: 4.58 to 4.95), and LMSM (incidence rate ratio, 1.74; 95% CI: 1.69 to 1.80), with the health benefits equally to reasonably distributed across groups (G, 0.32; 95% CI: 0.28 to 0.35). Relative to Status-quo, all other strategies reduced BMSM-WMSM and BMSM-LMSM disparities, but none reduced LMSM-WMSM disparities by 2035. Compared to Status-quo, strategy 3 reduced the most both incident infections (% infections averted: overall, 10.2%; BMSM, 32.4%; LMSM, 3.8%; WMSM, 3.5%) and HIV racial inequalities (G reduction, 0.08; 95% CI: 0.02 to 0.14). CONCLUSIONS: Microsimulation models developed with early, continuous stakeholder engagement and inputs yield powerful tools to guide policy implementation.