Dynamic Resilience Assessment for Urban Healthcare Infrastructure Operations Considering the Spatiotemporal Characteristics of Public Health Emergencies

Healthcare infrastructure (HI) is essential for ensuring access to quality medical services, controlling diseases, and enhancing human health and the overall livability of cities. As public health emergencies such as COVID-19 pose considerable challenges, effectively assessing and enhancing the resilience of HI operations has become imperative. Notably, public health emergencies exhibit significant spatial and temporal variability, and HI is a complex system comprising multiple units with various interactions such as geographic relationships and social cooperation, which need to be carefully considered in resilience assessment. This study proposes an integrated framework for dynamic resilience assessment of HI operations, considering spatiotemporal characteristics of emergencies and multiple interrelations among healthcare facilities. First, an improved susceptible-exposed-infectious-removed-hospitalized-Fangcang-dead model was developed to simulate various scenarios across different epidemic phases, given the spatial heterogeneity in outbreak locations and temporal variability in transmission capacity. Furthermore, considering the multiple interrelations among hospitals, the complex HI network was constructed by integrating geographic locations and social cooperation. Finally, under various outbreak scenarios, the cascading failure process of HI was accurately simulated to dynamically assess resilience during different time periods of the epidemic. The proposed method was applied to assess the resilience of HI operations during the COVID-19 pandemic in Wuhan, China, demonstrating its effectiveness and applicability. It was found that 38% of the hospitals in the entire HI system experienced failure during the initiation phase of the epidemic, and this percentage rose to 78% during the acceleration phase. Moreover, HI’s operational resilience presented obvious variations among different outbreak scenarios. Dynamic resilience assessment under various epidemic scenarios can inform the development of targeted optimization strategies for improving HI’s operational resilience, encompassing pre-emergency prevention, during-emergency response, and postemergency restoration. Our study provides valuable insights into enhancing HI’s operational resilience, which has obvious strengths in supporting the optimization of management strategies during public health emergencies.