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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.
  • Du Z; WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Zhang X; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, New Territories, Hong Kong Special Administrative Region, China.
  • Wang L; Department of Genetics, University of Cambridge, Cambridge, CB2 3EH, UK.
  • Yao S; Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (ASTAR), Singapore.
  • Bai Y; WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Tan Q; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, New Territories, Hong Kong Special Administrative Region, China.
  • Xu X; WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Pei S; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, New Territories, Hong Kong Special Administrative Region, China.
  • Xiao J; College of Information and Communication Engineering, Dalian Minzu University, Dalian City, Liaoning Province, China.
  • Tsang TK; Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York City, NY, USA.
  • Liao Q; WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Lau EHY; WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Wu P; WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Gao C; WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Cowling BJ; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, New Territories, Hong Kong Special Administrative Region, China.
China CDC Wkly ; 5(4): 71-75, 2023 Jan 27.
Article in English | MEDLINE | ID: covidwho-2240391
ABSTRACT
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.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Language: English Journal: China CDC Wkly Year: 2023 Document Type: Article Affiliation country: Ccdcw2023.014

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Language: English Journal: China CDC Wkly Year: 2023 Document Type: Article Affiliation country: Ccdcw2023.014