Characterizing Human Collective Behaviors During COVID-19 — Hong Kong SAR, China, 2020

Zhanwei Du, Xiao Zhang, Lin Wang, Sidan Yao, Yuan Bai, Qi Tan, Xiaoke Xu, Sen Pei, Jingyi Xiao, Tim K. Tsang, Qiuyan Liao, Eric H.Y. Lau, Peng Wu, Chao Gao, Benjamin J. Cowling

科研成果: 期刊稿件文章同行评审

6 引用 (Scopus)

摘要

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.

源语言英语
页(从-至)71-75
页数5
期刊China CDC Weekly
5
4
DOI
出版状态已出版 - 27 1月 2023

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