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Assessing urban resilience to public health disaster using the rough analytic hierarchy process method: A regional study in China

In the context of frequent occurrences of disasters worldwide, disaster-coping capability is imperative for risk reduction and contemporary emergency management. The global COVID-19 pandemic since 2020 has further highlighted the significance of resilience construction at different geographical scal...

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Detalles Bibliográficos
Autores principales: Liu, Zezhao, Ma, Rui, Wang, HuiJia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9671553/
http://dx.doi.org/10.1016/j.jnlssr.2021.12.003
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author Liu, Zezhao
Ma, Rui
Wang, HuiJia
author_facet Liu, Zezhao
Ma, Rui
Wang, HuiJia
author_sort Liu, Zezhao
collection PubMed
description In the context of frequent occurrences of disasters worldwide, disaster-coping capability is imperative for risk reduction and contemporary emergency management. The global COVID-19 pandemic since 2020 has further highlighted the significance of resilience construction at different geographical scales. Overall, the conceptual cognition of resilience in disaster management covers multiple elements and has diverse yielding on regional assessment. This study assesses the local resilience to the public health disaster in the prefecture-level cities, focusing on two dimensions consisting of vulnerability and capability in the targeted provincial region of Jiangsu in China. To this end, based on the vulnerability-capability framework, the Rough Analytic Hierarchy Process (Rough AHP) method was applied to the resilience assessment. Drawing upon the criteria derived from literature, the criteria weights were determined with the RAHP method and we assessed urban resilience with census data. In addition, the hierarchical factors contributing to urban resilience were determined using robustness analysis. This research provides constructive ideas for regional disaster reduction and contributes to the government's capability to improve urban resilience.
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spelling pubmed-96715532022-11-18 Assessing urban resilience to public health disaster using the rough analytic hierarchy process method: A regional study in China Liu, Zezhao Ma, Rui Wang, HuiJia Journal of Safety Science and Resilience Article In the context of frequent occurrences of disasters worldwide, disaster-coping capability is imperative for risk reduction and contemporary emergency management. The global COVID-19 pandemic since 2020 has further highlighted the significance of resilience construction at different geographical scales. Overall, the conceptual cognition of resilience in disaster management covers multiple elements and has diverse yielding on regional assessment. This study assesses the local resilience to the public health disaster in the prefecture-level cities, focusing on two dimensions consisting of vulnerability and capability in the targeted provincial region of Jiangsu in China. To this end, based on the vulnerability-capability framework, the Rough Analytic Hierarchy Process (Rough AHP) method was applied to the resilience assessment. Drawing upon the criteria derived from literature, the criteria weights were determined with the RAHP method and we assessed urban resilience with census data. In addition, the hierarchical factors contributing to urban resilience were determined using robustness analysis. This research provides constructive ideas for regional disaster reduction and contributes to the government's capability to improve urban resilience. China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. 2022-06 2021-12-31 /pmc/articles/PMC9671553/ http://dx.doi.org/10.1016/j.jnlssr.2021.12.003 Text en © 2022 China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Liu, Zezhao
Ma, Rui
Wang, HuiJia
Assessing urban resilience to public health disaster using the rough analytic hierarchy process method: A regional study in China
title Assessing urban resilience to public health disaster using the rough analytic hierarchy process method: A regional study in China
title_full Assessing urban resilience to public health disaster using the rough analytic hierarchy process method: A regional study in China
title_fullStr Assessing urban resilience to public health disaster using the rough analytic hierarchy process method: A regional study in China
title_full_unstemmed Assessing urban resilience to public health disaster using the rough analytic hierarchy process method: A regional study in China
title_short Assessing urban resilience to public health disaster using the rough analytic hierarchy process method: A regional study in China
title_sort assessing urban resilience to public health disaster using the rough analytic hierarchy process method: a regional study in china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9671553/
http://dx.doi.org/10.1016/j.jnlssr.2021.12.003
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