Dynamic Supply–Demand Matching and Spatial Mismatch Diagnosis of Emergency Beds in Designated Hospitals During Public Health Emergencies: A SEIQRDP-SG and 3SFCA-SMI Framework

In the context of public health emergencies (PHEs), conventional static indicators are insufficient for capturing the dynamic supply–demand relationship of emergency medical care. Grounded in adaptive cycle theory, this study proposes a integrated analytical framework that sequentially integrates supply baseline identification, disturbance impact simulation, mismatch diagnosis, and zoning-based response optimization. Taking 475 communities and 18 major designated hospitals in the Changsha metropolitan area as the empirical case, we integrate AHP-CRITIC evaluation, the SEIQRDP-SG model, and the 3SFCA-SMI method to identify the spatial mismatch of emergency-bed supply and demand and to delineate planning response zones. The results show that: (1) emergency-bed supply exhibits marked agglomeration and quasi-Pareto polarization, with the top three districts accounting for 75.83% of effective emergency beds; (2) under the core scenario of R0 = 5 with moderate intervention, peak bed demand in the metropolitan area reaches approximately 7835 beds around day 21, with high-demand communities emerging in high-density and high-mobility areas; and (3) although the overall supply–demand ratio is 1.34, 78% of communities cannot reach any designated hospital within 15 min, and the supply–demand pattern forms a compound spatial structure characterized by “central carrying, transitional mismatch, and peripheral weakness”. These findings indicate that the primary constraint on emergency medical resilience lies not in aggregate bed shortages alone, but in structural spatial mismatch jointly shaped by effective supply, dynamic demand, and transfer-time constraints. This study extends emergency medical facility evaluation from static assessment to dynamic matching and provides evidence for the layout of resilient “dual-use” medical facilities for routine and emergency conditions.