Zhang Jiaming, Wang Tao
School of Public Policy and Administration, Chongqing University, Shapingba District, Chongqing 400044, PR China.
Cities. 2023 May;136:104265. doi: 10.1016/j.cities.2023.104265. Epub 2023 Feb 28.
The COVID-19 pandemic, which lasted for three years, has had a great impact on the public health system, society and economy of cities, revealing the insufficiency of urban resilience under large-scale public health events (PHEs). Given that a city is a networked and multidimensional system with complex interactions, it is helpful to improve urban resilience under PHEs based on system thinking. Therefore, this paper proposes a dynamic and systematic urban resilience framework that incorporates four subsystems (governance, infrastructures, socioeconomy and energy-material flows). The composite index, system dynamics and epidemic simulation model are integrated into the framework to show the nonlinear relationships in the urban system and reflect the changing trend of urban resilience under PHEs. Then, urban resilience under different epidemic scenarios and response policy scenarios is calculated and discussed to provide some suggestions for decision-makers when faced with the trade-off between the control of PHEs and the maintenance of city operation. The paper concludes that control policies could be adjusted according to the characteristics of PHEs; strict control policies under a severe epidemic could lead to a significant decrease in urban resilience, while a more flexible control strategy can be adopted under a mild epidemic scenario to ensure the normal operation of urban functions. Moreover, the critical functions and impact factors of each subsystem are identified.
持续三年的新冠疫情对城市的公共卫生系统、社会和经济产生了巨大影响,暴露出大规模公共卫生事件(PHEs)下城市韧性的不足。鉴于城市是一个具有复杂相互作用的网络化多维度系统,基于系统思维来提高公共卫生事件下的城市韧性是有帮助的。因此,本文提出了一个动态的系统性城市韧性框架,该框架包含四个子系统(治理、基础设施、社会经济和能源物质流)。综合指数、系统动力学和疫情模拟模型被整合到该框架中,以展示城市系统中的非线性关系,并反映公共卫生事件下城市韧性的变化趋势。然后,计算并讨论了不同疫情情景和应对政策情景下的城市韧性,为决策者在面对公共卫生事件防控与城市运行维持之间的权衡时提供一些建议。本文得出结论,控制政策可根据公共卫生事件的特征进行调整;疫情严重时的严格控制政策可能导致城市韧性显著下降,而在疫情较轻的情景下可采用更灵活的控制策略以确保城市功能的正常运行。此外,还识别了每个子系统的关键功能和影响因素。