Research Progress and Improvement Ideas of Anti-Epidemic Resilience in China's Urban Communities.

In the post-epidemic era, China's urban communities are at the forefront of implementing the whole chain of accurate epidemic prevention and control. However, the uncertainty of COVID-19, the loopholes in community management and people's overly optimistic judgment of the epidemic have led to the frequent rebound of the epidemic and serious consequences. Existing studies have not yet formed a panoramic framework of community anti-epidemic work under the concept of resilience. Therefore, this article first summarizes the current research progress of resilient communities from three perspectives, including ideas and perspectives, theories and frameworks and methods and means, and summarizes the gap of the current research. Then, an innovative idea on the epidemic resilience of urban communities in China is put forward: (1) the evolution mechanism of community anti-epidemic resilience is described through the change law of dynamic networks; (2) the anti-epidemic resilience of urban communities is evaluated or predicted through the measurement criteria; (3) a simulation platform based on Multi-Agent and dynamic Bayesian networks simulates the interactive relationship between "epidemic disturbance-cost constraint--epidemic resilience"; (4) the anti-epidemic strategies are output intelligently to provide community managers with decision-making opinions on community epidemic prevention and control.

Key Influencing Factors and Optimization Strategy of Epidemic Resilience in Urban Communities-A Case Study of Nanjing, China.

COVID-19 has posed a significantly severe impact on both people's lives and the global economic development. Increasing the community epidemic resilience will considerably improve the national public health emergency response capacity from bottom to top. This study identifies the influencing factors of community epidemic resilience through systematic literature review under the 4R framework, then obtains the relationships of influencing factors through Interpretive structural model, and finally assesses the performance of epidemic resilience using PROMETHEE II method through empirical cases in Nanjing, China. The results show that: (1) Eight factors influencing the epidemic resilience of community are identified, and the economic level plays the root role; (2) Community epidemic resilience can be improved from robustness, rapidity, redundancy and resourcefulness aspects; (3) Through the empirical analysis, the epidemic resilience ranking of community can be displayed (Community D > T > S > F); (4) Additionally, the performance and sensitivity analysis of influencing factors in each community can be demonstrated. (5) Finally, four implications are proposed, namely, allocating public resources rationally, significantly increasing the economic level, ensuring the accuracy of information delivery and conducting disaster learning.