Abstract
Global pandemics, such as the Coronavirus Disease 2019 (COVID-19), have serious harmful effects on people′s physical health and mental well-being. It is imperative therefore that we seek to understand community resilience and identify ways to enhance this, especially within our cities and communities. Therefore, great emphasis is now placed on how cities prepare for and recover from such disasters, and community resilience has emerged as a key consideration. Drawing upon research on the theory of resilience, this study seeks to identify the factors that influence community resilience and to analyze their causation toward helping to manage the risks associated with the COVID-19 pandemic. Seventeen factors from the five dimensions of social capital, economic capital, physical environment, demographic characteristics, and institutional factors are used to construct an index system. This is used to establish the structural level and importance of each factor. Data were collected using a questionnaire survey involving 12,000 members of key community groups in the city of Wuhan. An interpretative structural model (ISM) combining the analytic hierarchy process (AHP) method was then used to obtain the multi-level hierarchical structure composed of direct factors, indirect factors, and fundamental factors. The results show that the income level, vulnerability of the population, and the built environment are the main factors that affect the resilience of communities affected by COVID-19. These findings provide useful guidance toward the effective planning and design of urban construction and infrastructure. The results are expected to be useful to inform future decision-making and toward the long term, sustainable management of the risks posed by COVID-19.
Highlights
In recent years, earthquakes, floods, droughts, public health epidemics, and other emergencies have become frequent occurrences [1]
interpretative structural model (ISM) was used to establish the hierarchical structure of community resilience to COVID-19, in order to consider the interactive network relationship among factors found to affect community resilience
The model can be used to effectively reflect the focus of efforts to improve urban community resilience. This approach toward community resilience assessment can be applied to group decision-making methods in the management of COVID-19 and can be applied to identify the interdependence and relationships among key factors affecting community resilience
Summary
Earthquakes, floods, droughts, public health epidemics, and other emergencies have become frequent occurrences [1]. Meng et al [30] conducted an elastic evaluation of an existing community in the city of Tianjin based on the data elastic evaluation system and found that the communities generally have community management problems, such as low awareness of disaster prevention, incomplete space construction, and inflexible emergency management; Liao et al [31] learned from international examples of community development, from the policy level to the national level They proposed recommendations for the development of community resilience in China based on five aspects: building open community space systems, coordinating community governance, building both a “smart community” and a “sponge community,” and improving a community’s self-organization ability. This supports the development of useful guidance toward improving the management of community resilience in the COVID-19 era
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