Spatial-temporal evolution characteristics and critical factors identification of urban resilience under public health emergencies

Public health emergencies have a massive impact on the safety of people's lives and property and the sustainable development of cities. Much scholarly attention has focused on the index system, measurement method, and operation mechanism of urban resilience. But those debates typically overlook the particularity of public health emergencies and the new features of urban data and dynamic intelligence. Building on this literature, this study takes 26 cities in the Yangtze River Delta Urban Agglomerations from 2000 to 2022 as research samples to scientifically propose a six-dimensional evaluation index system (economic, social, ecological, infrastructure, organizational, and institutional) by meta-analysis. This study also discusses the spatial-temporal static (dynamic) evolution law in depth based on the comprehensive weight of the CRITIC method and entropy method, and spatial Markov chain. Finally, with the help of combining the interpretative structural model and the complex network, critical factors are quantitatively identified from two aspects of node local and network global. This study proposes a novel approach to understanding urban resilience in public health emergencies. Furthermore, the evaluation index system, spatial-temporal evolution characteristics, and critical factor identification provide theoretical references and policy recommendations in developing safe development strategies for high-quality, safe, and resilient cities.