Statistical Models for Estimating Spatial and Sub-population HIV Epidemics

The global HIV response in 2025 is at a pivotal moment. While progress has been made, 1.3 million new infections occurred in 2023, far exceeding the 2020 target of 500,000. The 2021 Political Declaration on HIV emphasized the unmet prevention and treatment needs among different populations and regions as the key barrier to the 2030 target of fewer than 200,000 new infections. A critical bottleneck hindering an efficient and comprehensive response to HIV control is the lack of precise, actionable information derived from existing data. This proposal aims to address these information gaps to accelerate the fight against the entire HIV epidemic. We will leverage newly available HIV-related data and state-of-the-art methodologies to identify where and for whom the HIV response is lagging, in order to support the design of more effective and efficient policies and programs. Our proposal consists of the following specific aims: 1. Provide longitudinal and spatial estimates of key populations in countries with generalized HIV epidemics in sub-Saharan Africa (SSA). 2. Infer HIV incidence for sub-national areas and populations at high risk. 3. Produce freely available, open-source software to implement the proposed methods, and collaborate with global and local organizations to disseminate the methods and findings. Project Number: 1R01AI192205-01A1 | Fiscal Year: 2026 | NIH Institute/Center: National Institute of Allergy and Infectious Diseases (NIAID) | Principal Investigator: Le Bao | Institution: PENNSYLVANIA STATE UNIVERSITY, THE, UNIVERSITY PARK, PA | Award Amount: $842,720 | Activity Code: R01 | Study Section: Population and Public Health Approaches to HIV/AIDS Study Section[PPAH] View on NIH RePORTER: https://reporter.nih.gov/project-details/1R01AI19220501A1