Leveraging a community-driven approach and AI to advance structural changes and improve health

Modified Project Summary/Abstract Section Individuals with limited access to economic, health, and social opportunities face disproportionate risks of homelessness, poor healthcare access, and adverse physical and psychological outcomes. Although significant efforts across the United States have aimed to improve health through addressing social drivers, such as housing, healthcare access, and community conditions, these initiatives often fail to fully integrate the experiences of all communities. This project will examine how social conditions shape structural factors affecting health across the intergenerational community of Miami-Dade County, Florida. We will implement place-based structural interventions that establish shared, cross-sector community action planning and data systems, enhanced through artificial intelligence innovations. Guided by a Collective Impact framework, interventions will be co-designed with residents to ensure alignment with community needs and priorities. Longitudinal data will be collected using a mixed-methods approach, with emerging technologies applied to strengthen analysis and decision-making. The project will produce a community-led action plan to improve coordination of health and social services, strengthen resource allocation and build capacity for data-driven community decision-making. Long-term outcomes include measurable improvements in health and social conditions across the lifespan, as well as a sustainable, replicable model generalizable to other populations and geographic contexts.