HIV remains a persistent health threat in the United States, with over 32,000 new diagnoses in 2022 alone. This high number has been consistent over decades, highlighting the ongoing challenge of managing and reducing the spread of the virus. However, the burden of HIV is not evenly distributed across the country. Certain areas, including specific states, counties, cities, and neighborhoods, continue to experience significantly higher rates of new HIV diagnoses.

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To effectively reduce the burden of HIV, especially in areas with persistently high rates, it is crucial to accurately detect and forecast new HIV hotspots. Structural and social determinants of health play a key role in shaping these patterns. These determinants include the social, economic, and political systems that structure resources in the places where we live, work, and play. Factors such as housing distribution, poverty rates, density of religious organizations, unemployment, and healthcare access can all influence HIV transmission rates within a given area. Through the use of spatial data science and geospatial analyses, we develop models that predict where new HIV hotspots may emerge and identify the social determinants that predict these areas. We work closely with community organizations and health departments to leverage this data, enabling them to plan and implement effective HIV prevention interventions with the goal of reducing new diagnoses to 3,000 by 2030.