Assessing the spatial alignment between AED supply and spatiotemporal cardiac arrest risk in Beijing: a multi-source geospatial analysis

Automated External Defibrillators (AEDs) are critical medical devices for managing out-of-hospital cardiac arrest (OHCA). Their life-saving efficiency depends heavily on the precision of their spatial allocation. However, influenced by population aging and urban functional evolution, existing AED deployments are often biased toward public buildings and large transportation hubs. This results in an incomplete spatial alignment between supply and the actual, localized demand for cardiac arrest intervention. Drawing on Spatial Mismatch Theory and Ecosystem Service Supply-Demand Matching logic, this study proposes a multi-source geospatial data-driven framework for supply-demand assessment. We integrated high-resolution population grids, points of interest (POIs), and nighttime light imagery to construct a composite risk index, encompassing elderly population vulnerability, public activity-induced risk, and nighttime residential aggregation risk. AED supply accessibility was evaluated using road network topology based on the 4-minute total emergency response window, corresponding to a 3-minute effective accessibility threshold after accounting for approximately 1 min of AED operation time. Finally, a deployment priority index, was developed to identify emergency service “blind spots” through non-linear superposition. AED deployment in Beijing’s core urban area exhibits a pronounced “function-oriented” pattern, with high coverage in commercial centers and transportation hubs but structural supply gaps in high-risk residential zones. The comprehensive risk of cardiac arrest follows a “core-concentration and axial-extension” structure. Elderly population vulnerability is the primary driver of risk heterogeneity and carries the highest weight (0.3756). A Global Bivariate Moran’s I of -0.496 confirms a significant negative spatial autocorrelation between risk and supply gap. Local Bivariate LISA analysis identified multiple “High-Demand, High-Gap” (H-H) emergency blind spots, which represent critical nodes requiring prioritized “gap-filling” reinforcement. This study demonstrates that as foundational AED coverage reaches a phased milestone, the marginal utility of a “blanket deployment” mode solely pursuing scale expansion is diminishing. The observed incomplete spatial alignment between existing resources and the shifting risk landscape underscores the structural necessity of transitioning from a “facility-oriented” to a “people-oriented” planning paradigm. The transition toward precision reinforcement in identified high-risk areas represents a cost-effective pathway to enhance spatial coordination and health equity.