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Examining resilience of disaster response system in response to COVID-19

We examine the COVID-19 response in China by conceptualizing resilience from the complex adaptive system perspective, including a discussion of the factors contributing to the resilience of the disaster response system. Methodologically, a network-based model was employed to describe the disaster re...

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Detalles Bibliográficos
Autores principales: Guo, Xuesong, Kapucu, Naim, Huang, Jixin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9764218/
https://www.ncbi.nlm.nih.gov/pubmed/36569171
http://dx.doi.org/10.1016/j.ijdrr.2021.102239
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author Guo, Xuesong
Kapucu, Naim
Huang, Jixin
author_facet Guo, Xuesong
Kapucu, Naim
Huang, Jixin
author_sort Guo, Xuesong
collection PubMed
description We examine the COVID-19 response in China by conceptualizing resilience from the complex adaptive system perspective, including a discussion of the factors contributing to the resilience of the disaster response system. Methodologically, a network-based model was employed to describe the disaster response system. In addition to a traditional network analysis, the dynamics network analysis was conducted to assess the evolution of the disaster response system with a time slice analysis. This study presents theoretical and practical contributions to the field of disaster management by utilizing the complex adaptive system perspective and investigating context-specific resilience of a disaster response system.
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spelling pubmed-97642182022-12-20 Examining resilience of disaster response system in response to COVID-19 Guo, Xuesong Kapucu, Naim Huang, Jixin Int J Disaster Risk Reduct Article We examine the COVID-19 response in China by conceptualizing resilience from the complex adaptive system perspective, including a discussion of the factors contributing to the resilience of the disaster response system. Methodologically, a network-based model was employed to describe the disaster response system. In addition to a traditional network analysis, the dynamics network analysis was conducted to assess the evolution of the disaster response system with a time slice analysis. This study presents theoretical and practical contributions to the field of disaster management by utilizing the complex adaptive system perspective and investigating context-specific resilience of a disaster response system. Elsevier Ltd. 2021-06-01 2021-04-06 /pmc/articles/PMC9764218/ /pubmed/36569171 http://dx.doi.org/10.1016/j.ijdrr.2021.102239 Text en © 2021 Elsevier Ltd. All rights reserved. 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
Guo, Xuesong
Kapucu, Naim
Huang, Jixin
Examining resilience of disaster response system in response to COVID-19
title Examining resilience of disaster response system in response to COVID-19
title_full Examining resilience of disaster response system in response to COVID-19
title_fullStr Examining resilience of disaster response system in response to COVID-19
title_full_unstemmed Examining resilience of disaster response system in response to COVID-19
title_short Examining resilience of disaster response system in response to COVID-19
title_sort examining resilience of disaster response system in response to covid-19
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9764218/
https://www.ncbi.nlm.nih.gov/pubmed/36569171
http://dx.doi.org/10.1016/j.ijdrr.2021.102239
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