Equity-Aware Geospatial AI for Forecasting Demand-Driven Hospital Locations in Germany
This addresses the problem of equitable healthcare access for policymakers in Germany, though it appears incremental as it bridges existing domains like GeoAI and forecasting.
The paper tackles the problem of forecasting hospital demand and planning equitable facility locations in Germany through 2030 by developing an integrated framework that combines demographic and infrastructure data into an Equity Index, resulting in actionable recommendations for policymakers to minimize unmet need under budget and travel-time constraints.
This paper presents EA-GeoAI, an integrated framework for demand forecasting and equitable hospital planning in Germany through 2030. We combine district-level demographic shifts, aging population density, and infrastructure balances into a unified Equity Index. An interpretable Agentic AI optimizer then allocates beds and identifies new facility sites to minimize unmet need under budget and travel-time constraints. This approach bridges GeoAI, long-term forecasting, and equity measurement to deliver actionable recommendations for policymakers.