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Social Resilience Assessment for Urban System: A Case Study of COVID-19 Epidemic
7th China National Conference on Big Data and Social Computing, BDSC 2022 ; 1640 CCIS:40-56, 2022.
Article in English | Scopus | ID: covidwho-2173951
ABSTRACT
With the surge of deep uncertainties and multi-dimensional impacts of crisis events, social resilience assessment needs to advance the analysis of dynamic influencing process for urban system. To this end, this paper investigates the resilience assessment method of social resilience by using the differences analysis between capacities and demands. A gap analysis-based assessment method for social resilience is developed to quantify the resilience gap and levels, and a systemic resilience analysis framework is proposed to support overall analysis of urban systems. To verify the proposed method, we apply it to the novel coronavirus 2019 (COVID-19) epidemic in Shanghai during the period of February to May, 2022. Based on the data analysis of COVID-19-related cases, we compared the capacities and demands in urban medical system of patients transferring, admission and healing procedure. The fluctuations of resilience levels are examined and discussed. In addition, the resilience analysis of social systems and governance capacity in COVID-19 crisis are further carried out, and three-layer measures and procedure optimizations are introduced to build social resilience. The proposed resilience assessment method and systemic resilience management measures have potential implications and applications in the practical epidemic prevention and control. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Case report Language: English Journal: 7th China National Conference on Big Data and Social Computing, BDSC 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Case report Language: English Journal: 7th China National Conference on Big Data and Social Computing, BDSC 2022 Year: 2022 Document Type: Article