TY - JOUR
T1 - Characterizing Human Collective Behaviors During COVID-19 — Hong Kong SAR, China, 2020
AU - Du, Zhanwei
AU - Zhang, Xiao
AU - Wang, Lin
AU - Yao, Sidan
AU - Bai, Yuan
AU - Tan, Qi
AU - Xu, Xiaoke
AU - Pei, Sen
AU - Xiao, Jingyi
AU - Tsang, Tim K.
AU - Liao, Qiuyan
AU - Lau, Eric H.Y.
AU - Wu, Peng
AU - Gao, Chao
AU - Cowling, Benjamin J.
N1 - Publisher Copyright:
© 2023, Chinese Center for Disease Control and Prevention. All rights reserved.
PY - 2023/1/27
Y1 - 2023/1/27
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85162841203&partnerID=8YFLogxK
U2 - 10.46234/ccdcw2023.014
DO - 10.46234/ccdcw2023.014
M3 - 文章
AN - SCOPUS:85162841203
SN - 2096-7071
VL - 5
SP - 71
EP - 75
JO - China CDC Weekly
JF - China CDC Weekly
IS - 4
ER -
