ArticleTransport policy2021
COVid-19 influenced households' Interrupted Travel Schedules (COVHITS) survey: Lessons from the fall 2020 cycle.
Article in Transport policy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Application of Protection Motivation Theory to Quantify the Impact of Pandemic Fear on Anticipated Postpandemic Transit Usage.Transportation research record · 2023Article
- What happens when post-secondary programmes go virtual for COVID-19? Effects of forced telecommuting on travel demand of post-secondary students during the pandemic.Transportation research. Part A, Policy and practice · 2022Article
- Challenges for urban transport policy after the Covid-19 pandemic: Main findings from a survey in 20 European cities.Transport policy · 2022Article
- Research frontier of COVID-19 and passenger transport: A focus on policymaking.Transport policy · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The spread of the novel coronavirus disease-2019 (COVID-19) since early in 2020 has affected every aspect of daily life, including urban passenger travel patterns. Lockdowns to control the spread of COVID-19 created unprecedented travel demand contexts that have never been seen in modern history. So, it is essential to benchmark trends of travel behaviour, especially people's daily travel patterns that are necessary to develop a comprehensive understanding of the impacts of COVID-19. A multi-cycle benchmarking household travel study: the COVid-19 influenced Households' Interrupted Travel Schedules (COVHITS) Survey was implemented in the Greater Toronto Area with a random sample of over 4000 households. The results indicated a stark alteration in people's daily activity-travel patterns due to COVID-19. The pandemic caused a substantial decline in mobility in the study area. The average weekday household trip rate dropped from 5.2 to 2.0 trips. Transit modal shares suffered severely during the paramedic, while private car dependency was enhanced. Overall, transit modal share dropped from 17.3% to 8.1% in the study area, while the modal share of private cars increased from 70.8% to 74.1%. Factors such as having to work from home, ownership of private cars, and household incomes influenced mobility levels of the people in the study area during the pandemic. While overlooked, travel demand analysis can reveal effective strategies to curb the spread of such contagious diseases. An econometric model and analysis of sample data reveal several potential strategies. These include: (1) working/learning from home should be implemented until the end of the pandemic; (2) transit agencies should provide as much transit frequency as possible (particularly for bus routes) during peak hours to avoid crowding inside transit vehicles and project a positive image of public transit; and (3) strict restrictions should be implemented in regions with lower confirmed COVID-19 cases, as they became attractive destinations during the pandemic.
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