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The Influence of COVID-19 on Community Disaster Resilience
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 communitie...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795082/ https://www.ncbi.nlm.nih.gov/pubmed/33374318 http://dx.doi.org/10.3390/ijerph18010088 |
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author | Xu, Wenping Xiang, Lingli Proverbs, David Xiong, Shu |
author_facet | Xu, Wenping Xiang, Lingli Proverbs, David Xiong, Shu |
author_sort | Xu, Wenping |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7795082 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-77950822021-01-10 The Influence of COVID-19 on Community Disaster Resilience Xu, Wenping Xiang, Lingli Proverbs, David Xiong, Shu Int J Environ Res Public Health Article 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. MDPI 2020-12-24 2021-01 /pmc/articles/PMC7795082/ /pubmed/33374318 http://dx.doi.org/10.3390/ijerph18010088 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Xu, Wenping Xiang, Lingli Proverbs, David Xiong, Shu The Influence of COVID-19 on Community Disaster Resilience |
title | The Influence of COVID-19 on Community Disaster Resilience |
title_full | The Influence of COVID-19 on Community Disaster Resilience |
title_fullStr | The Influence of COVID-19 on Community Disaster Resilience |
title_full_unstemmed | The Influence of COVID-19 on Community Disaster Resilience |
title_short | The Influence of COVID-19 on Community Disaster Resilience |
title_sort | influence of covid-19 on community disaster resilience |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795082/ https://www.ncbi.nlm.nih.gov/pubmed/33374318 http://dx.doi.org/10.3390/ijerph18010088 |
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