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Author:

Zhang Nan (Zhang Nan.) (Scholars:张楠) | Jia Wei (Jia Wei.) (Scholars:魏佳) | Lei Hao (Lei Hao.) | Wang Peihua (Wang Peihua.) | Zhao Pengcheng (Zhao Pengcheng.) | Guo Yong (Guo Yong.) | Dung Chung-Hin (Dung Chung-Hin.) | Bu Zhongming (Bu Zhongming.) | Xue Peng (Xue Peng.) (Scholars:薛鹏) | Xie Jingchao (Xie Jingchao.) (Scholars:谢静超) | Zhang Yingping (Zhang Yingping.) | Cheng Reynold (Cheng Reynold.) | Li Yuguo (Li Yuguo.)

Indexed by:

PubMed

Abstract:

COVID-19 continues to threaten human life worldwide. We explored how human behaviours have been influenced by the COVID-19 pandemic in Hong Kong, and how the transmission of other respiratory diseases (e.g. influenza) has been influenced by human behaviour.We focused on the spread of COVID-19 and influenza infections based on reported COVID-19 cases and influenza surveillance data, and investigated the changes in human behaviour due to COVID-19 based on mass transit railway data and the data from a telephone survey. We did the simulation based on SEIR model to assess the risk reduction of influenza transmission caused by the changes in human behaviour.During the COVID-19 pandemic, the number of passengers fell by 52.0% compared with the same period in 2019. Residents spent 32.2% more time at home. Each person on average came into close contact with 17.6 and 7.1 people per day during the normal and pandemic periods, respectively. Students, workers, and older people reduced their daily number of close contacts by 83.0%, 48.1%, and 40.3%, respectively. The close contact rates in residences, workplaces, places of study, restaurants, shopping centres, markets, and public transport decreased by 8.3%, 30.8%, 66.0%, 38.5%, 48.6%, 41.0%, and 36.1%, respectively. Based on the simulation, these changes in human behaviours reduced the effective reproduction number of influenza by 63.1%.Human behaviours were significantly influenced by the COVID-19 pandemic in Hong Kong. Close contact control contributed more than 47% to the reduction in infection risk of COVID-19.

Keyword:

COVID-19 human behaviour non-pharmaceutical interventions influenza close contact

Author Community:

  • [ 1 ] [Zhang Nan]Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, China
  • [ 2 ] [Jia Wei]Department of Mechanical Engineering, The University of Hong Kong, Hong Kong SAR, China
  • [ 3 ] [Lei Hao]School of Public Health, Zhejiang University, Hangzhou, Zhejiang, China
  • [ 4 ] [Wang Peihua]Department of Mechanical Engineering, The University of Hong Kong, Hong Kong SAR, China
  • [ 5 ] [Zhao Pengcheng]Department of Mechanical Engineering, The University of Hong Kong, Hong Kong SAR, China
  • [ 6 ] [Guo Yong]Department of Building Science, Tsinghua University, Beijing, China
  • [ 7 ] [Dung Chung-Hin]Department of Mechanical Engineering, The University of Hong Kong, Hong Kong SAR, China
  • [ 8 ] [Bu Zhongming]Department of Energy and Environmental System Engineering, Zhejiang University of Science and Technology, Hangzhou, China
  • [ 9 ] [Xue Peng]Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, China
  • [ 10 ] [Xie Jingchao]Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, China
  • [ 11 ] [Zhang Yingping]Department of Building Science, Tsinghua University, Beijing, China
  • [ 12 ] [Cheng Reynold]Department of Computer Science, The University of Hong Kong, Hong Kong SAR, China
  • [ 13 ] [Li Yuguo]Department of Mechanical Engineering, The University of Hong Kong, Hong Kong SAR, China

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Source :

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America

ISSN: 1537-6591

Year: 2020

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 63

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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