Evidence map›Paper›PMID 33589850›Full record

ArticleCities (London, England)2021

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

Abstract read
In one paragraph

Article in Cities (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

49 citing papers in PubMed.

  1. Observational
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  18. Local travel behaviour under continuing COVID-19 waves- A proxy for pandemic fatigue?Transportation research interdisciplinary perspectives · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Nan ZhangBeijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, China.
Wei JiaDepartment of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.
Peihua WangDepartment of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.
Chung-Hin DungDepartment of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.
Pengcheng ZhaoDepartment of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.
Kathy LeungSchool of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China.
Boni SuChina Electric Power Planning & Engineering Institute, Beijing, China.
Reynold ChengDepartment of Computer Science, The University of Hong Kong, Hong Kong, China.
Yuguo LiDepartment of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 (

Indexed as

COVID-19Effective reproduction numberHuman behaviourLocal travel behaviourPublic transportSubway

Identifiers

PMID33589850
PMCPMC7877214

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.