Changes in local travel behaviour before and during the COVID-19 pandemic in Hong Kong.

Nan Zhang, Wei Jia, Peihua Wang, Chung-Hin Dung, Pengcheng Zhao, Kathy Leung, Boni Su, Reynold Cheng, Yuguo Li
Author Information
  1. Nan Zhang: Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, China.
  2. Wei Jia: Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.
  3. Peihua Wang: Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.
  4. Chung-Hin Dung: Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.
  5. Pengcheng Zhao: Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.
  6. Kathy Leung: School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China.
  7. Boni Su: China Electric Power Planning & Engineering Institute, Beijing, China.
  8. Reynold Cheng: Department of Computer Science, The University of Hong Kong, Hong Kong, China.
  9. Yuguo Li: Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.

Abstract

COVID-19 threatens the world. Social distancing is a significant factor in determining the spread of this disease, and social distancing is strongly affected by the local travel behaviour of people in large cities. In this study, we analysed the changes in the local travel behaviour of various population groups in Hong Kong, between 1 January and 31 March 2020, by using second-by-second smartcard data obtained from the Mass Transit Railway Corporation (MTRC) system. Due to the pandemic, local travel volume decreased by 43%, 49% and 59% during weekdays, Saturdays and Sundays, respectively. The local travel volumes of adults, children, students and senior citizens decreased by 42%, 86%, 73% and 48%, respectively. The local travel behaviour changes for adults and seniors between non-pandemic and pandemic times were greater than those between weekdays and weekends. The opposite was true for children and students. During the pandemic, the daily commute flow decreased by 42%. Local trips to shopping areas, amusement areas and borders decreased by 42%, 81% and 99%, respectively. The effective reproduction number ( ) of COVID-19 had the strongest association with daily population use of the MTR 7-8 days earlier.

Keywords

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Word Cloud

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