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

被引:7
作者
Du, Zhanwei [1 ]
Zhang, Xiao [2 ]
Wang, Lin [3 ]
Yao, Sidan [4 ]
Bai, Yuan [1 ,2 ]
Tan, Qi [1 ,2 ]
Xu, Xiaoke [5 ]
Pei, Sen [6 ]
Xiao, Jingyi [1 ]
Tsang, Tim K. [1 ]
Liao, Qiuyan [1 ]
Lau, Eric H. Y. [1 ,2 ]
Wu, Peng [1 ,2 ]
Gao, Chao [7 ]
Cowling, Benjamin J. [1 ,2 ]
机构
[1] Univ Hong Kong, Li Ka Shing Fac Med, WHO Collaborating Ctr Infect Dis Epidemiol & Cont, Sch Publ Hlth, Hong Kong, Peoples R China
[2] Hong Kong Sci & Technol Pk, Lab Data Discovery Hlth, Hong Kong, Peoples R China
[3] Univ Cambridge, Dept Genet, Cambridge CB2 3EH, England
[4] ASTAR, Inst High Performance Comp IHPC, Singapore, Singapore
[5] Dalian Minzu Univ, Coll Informat & Commun Engn, Dalian, Liaoning, Peoples R China
[6] Columbia Univ, Mailman Sch Publ Hlth, Dept Environm Hlth Sci, New York, NY USA
[7] Northwestern Polytech Univ, Sch Artificial Intelligence Opt & Elect iOpen, Xian, Shaanxi, Peoples R China
来源
CHINA CDC WEEKLY | 2023年 / 5卷 / 04期
基金
中国国家自然科学基金;
关键词
D O I
10.46234/ccdcw2023.014
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
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.
引用
收藏
页码:71 / +
页数:8
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