Spatial accessibility and equity of emergency medical services: Evidence from Ningbo
Minxia Fu, Jieyi Guan, Yixi Zheng, Xingchuan Gao, Wenwan Jin, Pengtao WangBackground
Timely access to emergency medical services (EMS) is essential for improving survival outcomes and public health. In rapidly urbanizing Chinese cities, disparities in EMS accessibility are increasingly shaped by the spatial distribution of hospitals, population concentration, transport infrastructure, and built environment conditions. However, relatively few studies have simultaneously compared emergency and non-emergency medical accessibility and examined their spatial equity and influencing factors in medium-sized coastal cities. This study evaluates the spatial accessibility, equity, and clustering characteristics of EMS in Ningbo, China, and identifies the key built environment factors influencing these patterns.
Methods
The shortest travel time model, based on API data, was employed to measure EMS accessibility for both emergency (ambulance) and non-emergency (public transport) scenarios across five core urban districts of Ningbo. The Lorenz curve and Gini coefficient were applied to assess healthcare equity. We used global Moran’s I and local indicators of spatial association (LISA) to explore spatial clustering and a multiscale geographically weighted regression (MGWR) model to analyze spatial heterogeneity in influencing factors across built environment dimensions.
Results
Both emergency and non-emergency medical services exhibited significant spatial disparities, decreasing gradually from the city center toward the periphery. The Gini coefficients for emergency and non-emergency models were 0.5156 and 0.4898, respectively, indicating substantial inequity. Strong spatial clustering was observed (global Moran’s I = 0.846, p < 0.01), with high-value clusters concentrated in central districts and low-value clusters in mountainous outskirts. MGWR results revealed that accessibility was positively affected by the number of bus stops, road density, bus route density, and distance to the Central Business District (CBD), but negatively impacted by building density and development intensity. The MGWR model’s explanatory power (R 2 = 0.584) demonstrated significant spatial heterogeneity in these relationships. Building density and bus route density exerted the strongest local effects among the eleven built environment indicators.
Conclusion
EMS accessibility in Ningbo exhibits evident spatial inequality and clustering characteristics. Peripheral and mountainous areas remain disadvantaged, especially under non-emergency public transport conditions. Improving road connectivity, expanding public transit coverage, optimizing hospital and EMS resource allocation, and strengthening services in underserved areas can help reduce healthcare accessibility inequities. These findings provide an empirical foundation for optimizing EMS resource allocation for urban policymakers as well as offer practical insights for other rapidly urbanizing cities facing similar challenges.