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Impact of COVID-19 pandemic on mobility in ten countries and associated perceived risk for all transport modes

Author

Listed:
  • Diego Maria Barbieri
  • Baowen Lou
  • Marco Passavanti
  • Cang Hui
  • Inge Hoff
  • Daniela Antunes Lessa
  • Gaurav Sikka
  • Kevin Chang
  • Akshay Gupta
  • Kevin Fang
  • Arunabha Banerjee
  • Brij Maharaj
  • Louisa Lam
  • Navid Ghasemi
  • Bhaven Naik
  • Fusong Wang
  • Ali Foroutan Mirhosseini
  • Sahra Naseri
  • Zhuangzhuang Liu
  • Yaning Qiao
  • Andrew Tucker
  • Kasun Wijayaratna
  • Prince Peprah
  • Solomon Adomako
  • Lei Yu
  • Shubham Goswami
  • Hao Chen
  • Benan Shu
  • Amir Hessami
  • Montasir Abbas
  • Nithin Agarwal
  • Taha Hossein Rashidi

Abstract

The restrictive measures implemented in response to the COVID-19 pandemic have triggered sudden massive changes to travel behaviors of people all around the world. This study examines the individual mobility patterns for all transport modes (walk, bicycle, motorcycle, car driven alone, car driven in company, bus, subway, tram, train, airplane) before and during the restrictions adopted in ten countries on six continents: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. This cross-country study also aims at understanding the predictors of protective behaviors related to the transport sector and COVID-19. Findings hinge upon an online survey conducted in May 2020 (N = 9,394). The empirical results quantify tremendous disruptions for both commuting and non-commuting travels, highlighting substantial reductions in the frequency of all types of trips and use of all modes. In terms of potential virus spread, airplanes and buses are perceived to be the riskiest transport modes, while avoidance of public transport is consistently found across the countries. According to the Protection Motivation Theory, the study sheds new light on the fact that two indicators, namely income inequality, expressed as Gini index, and the reported number of deaths due to COVID-19 per 100,000 inhabitants, aggravate respondents’ perceptions. This research indicates that socio-economic inequality and morbidity are not only related to actual health risks, as well documented in the relevant literature, but also to the perceived risks. These findings document the global impact of the COVID-19 crisis as well as provide guidance for transportation practitioners in developing future strategies.

Suggested Citation

  • Diego Maria Barbieri & Baowen Lou & Marco Passavanti & Cang Hui & Inge Hoff & Daniela Antunes Lessa & Gaurav Sikka & Kevin Chang & Akshay Gupta & Kevin Fang & Arunabha Banerjee & Brij Maharaj & Louisa, 2021. "Impact of COVID-19 pandemic on mobility in ten countries and associated perceived risk for all transport modes," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-18, February.
  • Handle: RePEc:plo:pone00:0245886
    DOI: 10.1371/journal.pone.0245886
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    References listed on IDEAS

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    2. Rossetti, Tomás & Daziano, Ricardo A., 2024. "Crowding multipliers on shared transportation in New York City: The effects of COVID-19 and implications for a sustainable future," Transport Policy, Elsevier, vol. 145(C), pages 224-236.
    3. Li, Xinming & Hossein Rashidi, Taha & Koo, Tay T.R., 2023. "Tourists’ travel mode and length of stay: Application of a fully nested Archimedean copula structure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 172(C).
    4. Sukchan Hong & Byungyun Yang, 2025. "Analyzing the Impact of Land-Use Characteristics and Demographic Factors on Spatial Variations in Public Bus Usage: A Comparison of Pre- and During COVID-19 Periods," Land, MDPI, vol. 14(5), pages 1-21, May.
    5. Yukun Gao & Pengjun Zhao, 2024. "Tracing long-term commute mode choice shifts in Beijing: four years after the COVID-19 pandemic," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-18, December.
    6. Camila Balbontin & David A. Hensher & Matthew J. Beck, 2024. "Relationship between commuting and non-commuting travel activity under the growing incidence of working from home and people’s attitudes towards COVID-19," Transportation, Springer, vol. 51(6), pages 2225-2251, December.
    7. Barbour, Natalia & Abdel-Aty, Mohamed & Sevim, Alican, 2024. "Intended work from home frequency after the COVID-19 pandemic and the role of socio-demographic, psychological, disability, and work-related factors," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    8. Balbontin, Camila & Hensher, David A. & Beck, Matthew J., 2024. "The influence of working from home and underlying attitudes on the number of commuting and non-commuting trips by workers during 2020 and 2021 pre- and post-lockdown in Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    9. Nguyen-Phuoc, Duy Quy & Pham, Son Truong & Nguyen, Thao Phuong Thi & Su, Diep Ngoc & Luu, Tuan Trong & Oviedo-Trespalacios, Oscar, 2025. "Exploring the switch to urban train services: The impact of perceived accessibility and its moderating effects," Transportation Research Part A: Policy and Practice, Elsevier, vol. 191(C).
    10. Borowska-Stefańska, Marta & Dulebenets, Maxim A. & Horňák, Marcel & Kowalski, Michał & Kozłowski, Dominik & Turoboś, Filip & Wiśniewski, Szymon, 2023. "Assessing the effects of Sunday shopping restrictions on urban mobility patterns in Poland," Journal of Transport Geography, Elsevier, vol. 113(C).
    11. Wang, Sicheng & Huang, Xiao & Shen, Qing, 2024. "Disparities in resilience and recovery of ridesourcing usage during COVID-19," Journal of Transport Geography, Elsevier, vol. 114(C).

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