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Characterizing Human Collective Behaviors During COVID-19 — Hong Kong SAR, China, 2020
WHAT IS ALREADY KNOWN ABOUT THIS TOPIC? People are likely to engage in collective behaviors online during extreme events, such as the coronavirus disease 2019 (COVID-19) crisis, to express awareness, take action, and work through concerns. WHAT IS ADDED BY THIS REPORT? This study offers a framework...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Editorial Office of CCDCW, Chinese Center for Disease Control and Prevention
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9902758/ https://www.ncbi.nlm.nih.gov/pubmed/36777899 http://dx.doi.org/10.46234/ccdcw2023.014 |
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author | Du, Zhanwei Zhang, Xiao Wang, Lin Yao, Sidan Bai, Yuan Tan, Qi Xu, Xiaoke Pei, Sen Xiao, Jingyi Tsang, Tim K. Liao, Qiuyan Lau, Eric H. Y. Wu, Peng Gao, Chao Cowling, Benjamin J. |
author_facet | Du, Zhanwei Zhang, Xiao Wang, Lin Yao, Sidan Bai, Yuan Tan, Qi Xu, Xiaoke Pei, Sen Xiao, Jingyi Tsang, Tim K. Liao, Qiuyan Lau, Eric H. Y. Wu, Peng Gao, Chao Cowling, Benjamin J. |
author_sort | Du, Zhanwei |
collection | PubMed |
description | WHAT IS ALREADY KNOWN ABOUT THIS TOPIC? People are likely to engage in collective behaviors online during extreme events, such as the coronavirus disease 2019 (COVID-19) crisis, to express awareness, take action, and work through concerns. WHAT IS ADDED BY THIS REPORT? This study offers a framework for evaluating interactions among individuals’ emotions, perceptions, and online behaviors in Hong Kong Special Administrative Region (SAR) during the first two waves of COVID-19 (February to June 2020). Its results indicate a strong correlation between online behaviors, such as Google searches, and the real-time reproduction numbers. To validate the model’s output of risk perception, this investigation conducted 10 rounds of cross-sectional telephone surveys on 8,593 local adult residents from February 1 through June 20 in 2020 to quantify risk perception levels over time. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE? Compared to the survey results, the estimates of the risk perception of individuals using our network-based mechanistic model capture 80% of the trend of people’s risk perception (individuals who are worried about being infected) during the studied period. We may need to reinvigorate the public by involving people as part of the solution that reduced the risk to their lives. |
format | Online Article Text |
id | pubmed-9902758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Editorial Office of CCDCW, Chinese Center for Disease Control and Prevention |
record_format | MEDLINE/PubMed |
spelling | pubmed-99027582023-02-10 Characterizing Human Collective Behaviors During COVID-19 — Hong Kong SAR, China, 2020 Du, Zhanwei Zhang, Xiao Wang, Lin Yao, Sidan Bai, Yuan Tan, Qi Xu, Xiaoke Pei, Sen Xiao, Jingyi Tsang, Tim K. Liao, Qiuyan Lau, Eric H. Y. Wu, Peng Gao, Chao Cowling, Benjamin J. China CDC Wkly Preplanned Studies WHAT IS ALREADY KNOWN ABOUT THIS TOPIC? People are likely to engage in collective behaviors online during extreme events, such as the coronavirus disease 2019 (COVID-19) crisis, to express awareness, take action, and work through concerns. WHAT IS ADDED BY THIS REPORT? This study offers a framework for evaluating interactions among individuals’ emotions, perceptions, and online behaviors in Hong Kong Special Administrative Region (SAR) during the first two waves of COVID-19 (February to June 2020). Its results indicate a strong correlation between online behaviors, such as Google searches, and the real-time reproduction numbers. To validate the model’s output of risk perception, this investigation conducted 10 rounds of cross-sectional telephone surveys on 8,593 local adult residents from February 1 through June 20 in 2020 to quantify risk perception levels over time. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE? Compared to the survey results, the estimates of the risk perception of individuals using our network-based mechanistic model capture 80% of the trend of people’s risk perception (individuals who are worried about being infected) during the studied period. We may need to reinvigorate the public by involving people as part of the solution that reduced the risk to their lives. Editorial Office of CCDCW, Chinese Center for Disease Control and Prevention 2023-01-27 /pmc/articles/PMC9902758/ /pubmed/36777899 http://dx.doi.org/10.46234/ccdcw2023.014 Text en Copyright and License information: Editorial Office of CCDCW, Chinese Center for Disease Control and Prevention 2023 https://creativecommons.org/licenses/by-nc-sa/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/ (https://creativecommons.org/licenses/by-nc-sa/4.0/) |
spellingShingle | Preplanned Studies Du, Zhanwei Zhang, Xiao Wang, Lin Yao, Sidan Bai, Yuan Tan, Qi Xu, Xiaoke Pei, Sen Xiao, Jingyi Tsang, Tim K. Liao, Qiuyan Lau, Eric H. Y. Wu, Peng Gao, Chao Cowling, Benjamin J. Characterizing Human Collective Behaviors During COVID-19 — Hong Kong SAR, China, 2020 |
title | Characterizing Human Collective Behaviors During COVID-19 — Hong Kong SAR, China, 2020 |
title_full | Characterizing Human Collective Behaviors During COVID-19 — Hong Kong SAR, China, 2020 |
title_fullStr | Characterizing Human Collective Behaviors During COVID-19 — Hong Kong SAR, China, 2020 |
title_full_unstemmed | Characterizing Human Collective Behaviors During COVID-19 — Hong Kong SAR, China, 2020 |
title_short | Characterizing Human Collective Behaviors During COVID-19 — Hong Kong SAR, China, 2020 |
title_sort | characterizing human collective behaviors during covid-19 — hong kong sar, china, 2020 |
topic | Preplanned Studies |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9902758/ https://www.ncbi.nlm.nih.gov/pubmed/36777899 http://dx.doi.org/10.46234/ccdcw2023.014 |
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