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Improving social resilience amid the COVID-19 epidemic: A system dynamics model
Social resilience is a key factor in disaster management, but compared to resilience in other fields, research on social resilience is still limited to assessment or evaluation, and there is still a lack of dynamic and procedural research, which is also a challenge. This article constructs a causal...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635487/ https://www.ncbi.nlm.nih.gov/pubmed/37943771 http://dx.doi.org/10.1371/journal.pone.0294108 |
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author | Kou, Chenhuan Yang, Xiuli |
author_facet | Kou, Chenhuan Yang, Xiuli |
author_sort | Kou, Chenhuan |
collection | PubMed |
description | Social resilience is a key factor in disaster management, but compared to resilience in other fields, research on social resilience is still limited to assessment or evaluation, and there is still a lack of dynamic and procedural research, which is also a challenge. This article constructs a causal feedback model and a system dynamics model of social resilience during the COVID-19 epidemic, so as to analyze the dynamic characteristics and improvement path of social resilience. After verifying the effectiveness of the model, model simulation is conducted and the following important conclusions are drawn: social resilience dynamically changes during the research cycle and is influenced by social entity behavior and social mechanisms; The sensitivity factors for the two variables that measure social resilience, namely panic degree and damage degree, are the real-time information acquisition of public and the epidemic awareness of local government, respectively. Therefore, the path to enhancing social resilience should be pursued from both the public and government perspectives, including improving the public’s ability to access real-time information, increasing the timeline of government information disclosure, and enhancing local governments’ understanding and awareness of the epidemic. |
format | Online Article Text |
id | pubmed-10635487 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-106354872023-11-10 Improving social resilience amid the COVID-19 epidemic: A system dynamics model Kou, Chenhuan Yang, Xiuli PLoS One Research Article Social resilience is a key factor in disaster management, but compared to resilience in other fields, research on social resilience is still limited to assessment or evaluation, and there is still a lack of dynamic and procedural research, which is also a challenge. This article constructs a causal feedback model and a system dynamics model of social resilience during the COVID-19 epidemic, so as to analyze the dynamic characteristics and improvement path of social resilience. After verifying the effectiveness of the model, model simulation is conducted and the following important conclusions are drawn: social resilience dynamically changes during the research cycle and is influenced by social entity behavior and social mechanisms; The sensitivity factors for the two variables that measure social resilience, namely panic degree and damage degree, are the real-time information acquisition of public and the epidemic awareness of local government, respectively. Therefore, the path to enhancing social resilience should be pursued from both the public and government perspectives, including improving the public’s ability to access real-time information, increasing the timeline of government information disclosure, and enhancing local governments’ understanding and awareness of the epidemic. Public Library of Science 2023-11-09 /pmc/articles/PMC10635487/ /pubmed/37943771 http://dx.doi.org/10.1371/journal.pone.0294108 Text en © 2023 Kou, Yang https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Kou, Chenhuan Yang, Xiuli Improving social resilience amid the COVID-19 epidemic: A system dynamics model |
title | Improving social resilience amid the COVID-19 epidemic: A system dynamics model |
title_full | Improving social resilience amid the COVID-19 epidemic: A system dynamics model |
title_fullStr | Improving social resilience amid the COVID-19 epidemic: A system dynamics model |
title_full_unstemmed | Improving social resilience amid the COVID-19 epidemic: A system dynamics model |
title_short | Improving social resilience amid the COVID-19 epidemic: A system dynamics model |
title_sort | improving social resilience amid the covid-19 epidemic: a system dynamics model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635487/ https://www.ncbi.nlm.nih.gov/pubmed/37943771 http://dx.doi.org/10.1371/journal.pone.0294108 |
work_keys_str_mv | AT kouchenhuan improvingsocialresilienceamidthecovid19epidemicasystemdynamicsmodel AT yangxiuli improvingsocialresilienceamidthecovid19epidemicasystemdynamicsmodel |