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Updated: Sep 8, 2025

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
Using Microsimulation Modeling to Inform EHE Implementation Strategies in Los Angeles County
Emmanuel F Drabo1, Corrina Moucheraud2,3, Anthony Nguyen4
1Department of Health Policy and Management, John Hopkins Bloomberg School of Public Health, Baltimore, MD.
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.
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