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Community Resilience and COVID-19: A Fuzzy-Set Qualitative Comparative Analysis of Resilience Attributes in 16 Countries

The COVID-19 pandemic has caused massive disruptions to governments and societies across the world. While public healthcare systems have come under immense pressure, public trust in governments and institutions are also in decline. In this paper, we seek to assess the resilience of policy systems an...

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Detalles Bibliográficos
Autores principales: Yi, Fangxin, Woo, Jun Jie, Zhang, Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9819088/
https://www.ncbi.nlm.nih.gov/pubmed/36612795
http://dx.doi.org/10.3390/ijerph20010474
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author Yi, Fangxin
Woo, Jun Jie
Zhang, Qiang
author_facet Yi, Fangxin
Woo, Jun Jie
Zhang, Qiang
author_sort Yi, Fangxin
collection PubMed
description The COVID-19 pandemic has caused massive disruptions to governments and societies across the world. While public healthcare systems have come under immense pressure, public trust in governments and institutions are also in decline. In this paper, we seek to assess the resilience of policy systems and processes in 16 countries during the COVID-19 pandemic through the use of fuzzy-set Qualitative Comparative Analysis (fsQCA). We focus specifically on robustness, preparedness, social capital, and institutional strength as key attributes of community resilience at city-level. Our analysis of the data reveals that COVID-19 resilience is dependent on a combination of factors, with a multi-factorial approach to policy design and governance necessary for effective pandemic and disaster recovery.
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spelling pubmed-98190882023-01-07 Community Resilience and COVID-19: A Fuzzy-Set Qualitative Comparative Analysis of Resilience Attributes in 16 Countries Yi, Fangxin Woo, Jun Jie Zhang, Qiang Int J Environ Res Public Health Article The COVID-19 pandemic has caused massive disruptions to governments and societies across the world. While public healthcare systems have come under immense pressure, public trust in governments and institutions are also in decline. In this paper, we seek to assess the resilience of policy systems and processes in 16 countries during the COVID-19 pandemic through the use of fuzzy-set Qualitative Comparative Analysis (fsQCA). We focus specifically on robustness, preparedness, social capital, and institutional strength as key attributes of community resilience at city-level. Our analysis of the data reveals that COVID-19 resilience is dependent on a combination of factors, with a multi-factorial approach to policy design and governance necessary for effective pandemic and disaster recovery. MDPI 2022-12-28 /pmc/articles/PMC9819088/ /pubmed/36612795 http://dx.doi.org/10.3390/ijerph20010474 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yi, Fangxin
Woo, Jun Jie
Zhang, Qiang
Community Resilience and COVID-19: A Fuzzy-Set Qualitative Comparative Analysis of Resilience Attributes in 16 Countries
title Community Resilience and COVID-19: A Fuzzy-Set Qualitative Comparative Analysis of Resilience Attributes in 16 Countries
title_full Community Resilience and COVID-19: A Fuzzy-Set Qualitative Comparative Analysis of Resilience Attributes in 16 Countries
title_fullStr Community Resilience and COVID-19: A Fuzzy-Set Qualitative Comparative Analysis of Resilience Attributes in 16 Countries
title_full_unstemmed Community Resilience and COVID-19: A Fuzzy-Set Qualitative Comparative Analysis of Resilience Attributes in 16 Countries
title_short Community Resilience and COVID-19: A Fuzzy-Set Qualitative Comparative Analysis of Resilience Attributes in 16 Countries
title_sort community resilience and covid-19: a fuzzy-set qualitative comparative analysis of resilience attributes in 16 countries
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9819088/
https://www.ncbi.nlm.nih.gov/pubmed/36612795
http://dx.doi.org/10.3390/ijerph20010474
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