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Post-pandemic transit commute: Lessons from focus group discussions on the experience of essential workers during COVID-19

Ashour, L. A., Shen, Q., Moudon, A., Cai, M., Wang, Y., & Brown, M. (2024). Post-pandemic transit commute: Lessons from focus group discussions on the experience of essential workers during COVID-19. Journal of Transport Geography, 116. https://doi.org/10.1016/j.jtrangeo.2024.103832

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Abstract

Public transit services, which provide a critical lifeline for many essential workers, were severely interrupted during the COVID-19 pandemic. As institutions gradually return to normal in-person operations, it is critical to understand how the pandemic affected essential workers' commute and what it will take to ensure the effective recovery of transit ridership and enhance the long-term resiliency and equity of public transportation systems for those who need it the most. This study used focus group discussions with essential workers who were pre-pandemic transit riders to understand how the COVID-19 pandemic has impacted their commute perceptions, experiences, motives, and challenges and explore the potential changes in their travel behavior post-pandemic. We used NVivo 12 Pro to conduct a thematic analysis of the transcripted discussion data and examined patterns of commute mode change with respect to participants' attributes, including job type, home location, and gender. The results show that public transit had multiple reliability and frequency challenges during the pandemic, which resulted in most participants switching away from public transportation. With the increased availability of hybrid remote work and pandemic-related parking policies, driving emerged as a safer and more affordable commute mode for many pre-pandemic transit riders, rendering transit services less efficient for those who continued to rely on it. Planning for post-COVID resilient and reliable mobility requires a major rethinking of providing an efficient and effective transport system and a more fundamental approach to long-term public transport policy. To recover transit ridership, transit agencies need to ensure transit service availability and provide reliable transit information through smartphone apps. Similarly, transit agencies need to coordinate with other employers to provide free or heavily subsidized transit passes, to facilitate the recovery of transit demand effectively.

Keywords

Essential workers; Commute; Public transit; Focus group discussions; COVID-19 pandemic; Post-pandemic

Examining commute mode choice of essential workers before and during the COVID-19 pandemic – A case study of the University of Washington

Cai, M., Shen, Q., Wang, Y., Brown, M., Ban, X., & Ashour, L. A. (2024). Examining commute mode choice of essential workers before and during the COVID-19 pandemic – A case study of the University of Washington. Case Studies on Transport Policy, 15, 101129-. https://doi.org/10.1016/j.cstp.2023.101129

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Abstract

During disruptive events and major crises such as the COVID-19 pandemic, essential workers, defined in this study as employees who must continue to make frequent commute trips, play a critical role in maintaining the basic function of society. It is therefore vital for transportation planners and policymakers to ensure that adequate mobility services are provided to meet the travel needs of this group of workers. To better understand essential workers' mobility barriers and inform future transportation policy, this research examines their pre-and during-pandemic commutes, as well as prospects on future commuting, using data from the Transportation Needs Assessment Survey conducted by the University of Washington in Seattle. The results show that, first, over 60% of pre-pandemic public transit riders switched to other modes, especially driving alone. In contrast, almost all the essential workers who drove alone, biked, or walked before the pandemic continued to do so during the pandemic. Second, the shift to driving alone was most pronounced among essential workers with high incomes, whereas public transit remained as a primary mode choice of lower-income groups. As travel distance increased, the probability of driving alone over public transit also went up, although the relationship was not linear. We did not find consistently significant associations between mode choice and other sociodemographic variables. Finally, our analysis indicated that most essential workers anticipated to return to their pre-pandemic commute frequency and mode choice when the pandemic is under control. Transportation planners and policymakers can facilitate mobility for essential workers through planning and policy innovations, especially during disruptive events and major crises.

Keywords

Essential workers; Transportation equity; Mode choice; Commuting; COVID-19

Developing a multi-criteria prioritization tool to catalyze TOD on publicly owned land areas

Cai, M., Acolin, A., Moudon, A. V., & Shen, Q. (2023). Developing a multi-criteria prioritization tool to catalyze TOD on publicly owned land areas. Cities, 143, 104606-. https://doi.org/10.1016/j.cities.2023.104606

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Abstract

Public agencies can take a leading role in catalyzing TOD by making land available to developers (selling or leasing land, potentially below market prices). In particular, park-and-ride areas that are publicly owned can be leveraged to support TOD uses, such as affordable housing, office space, small businesses, and mixed-use buildings given their convenient access to transit systems and often large land areas. However, few previous studies have discussed the use of publicly owned park-and-rides, which are an important component of publicly owned land, as a catalyst for TOD. To fill the gap in the literature and effectively support TOD planning, this research developed a multi-criteria prioritization tool to identify the most promising locations for TOD and tested it at three park-and-ride sites owned by the Washington State Department of Transportation. The tool was developed through the Delphi process, which is an effective and inexpensive approach to evaluate relevant indicators by synthesizing the opinions of experts from various backgrounds. Five categories with a total of 14 TOD indicators, including transit supportive land-use zoning, job accessibility, land price, land-use mix, and household income, were selected as measures of TOD suitability. The importance of these indicators varied with three different TOD scenarios: (1) emphasis on affordable housing, (2) emphasis on market-rate housing, and (3) emphasis on mixed-use development. Using the calculated suitability scores, this tool can prioritize potential TOD sites for further review.

Keywords

TOD; Delphi method; Multi-criteria planning tool; Multi-sources geospatial data; Publicly owned land

Population Mobility and the Transmission Risk of the Covid-19 in Wuhan, China

Luo, Minghai; Qin, Sixian; Tan, Bo; Cai, Mingming; Yue, Yufeng; Xiong, Qiangqiang. (2021). Population Mobility and the Transmission Risk of the Covid-19 in Wuhan, China. Isprs International Journal Of Geo-information, 10(6).

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Abstract

At the beginning of 2020, a suddenly appearing novel coronavirus (COVID-19) rapidly spread around the world. The outbreak of the COVID-19 pandemic in China occurred during the Spring Festival when a large number of migrants traveled between cities, which greatly increased the infection risk of COVID-19 across the country. Financially supported by the Wuhan government, and based on cellphone signaling data from Unicom (a mobile phone carrier) and Baidu location-based data, this paper analyzed the effects that city dwellers, non-commuters, commuters, and people seeking medical services had on the transmission risk of COVID-19 in the early days of the pandemic in Wuhan. The paper also evaluated the effects of the city lockdown policy on the spread of the pandemic outside and inside Wuhan. The results show that although the daily business activities in the South China Seafood Wholesale Market and nearby commuters' travel behaviors concentrated in the Hankou area, a certain proportion of these people were distributed in the Wuchang and Hanyang areas. The areas with relatively high infection risks of COVID-19 were scattered across Wuhan during the early outbreak of the pandemic. The lockdown in Wuhan closed the passageways of external transport at the very beginning, largely decreasing migrant population and effectively preventing the spread of the pandemic to the outside. However, the Wuhan lockdown had little effect on preventing the spread of the pandemic within Wuhan at that time. During this period, a large amount of patients who went to hospitals for medical services were exposed to a high risk of cross-infection without precaution awareness. The pandemic kept dispersing in three towns until the improvement of the capacity of medical treatment, the management of closed communities, the national support to Wuhan, and the implementation of a series of emergency responses at the same time. The findings in this paper reveal the spatiotemporal features of the dispersal of infection risk of COVID-19 and the effects of the prevention and control measures during the early days of the pandemic. The findings were adopted by the Wuhan government to make corresponding policies and could also provide supports to the control of the pandemic in the other regions and countries.

Keywords

Covid-19; Covid-19 Pandemic; Sars-cov-2; Seafood Markets; Pandemics; Cell Phones; City Dwellers; Wuhan (china); Big Data; Novel Coronavirus; Population Mobility; Risk Analysis; Zika Virus; Diseases; Africa; Impact; Ebola; Spain; Passageways; Smartphones; Investigations; Disease Control; Emergency Response; Health Services; Viral Diseases; Policies; Outbreaks; Emergency Preparedness; Risk; Seafood; Coronaviruses; Medical Treatment; Transmission; Commuting; Dispersion; Dispersal; Infections; Cross-infection; Epidemics; Health Risks; Disease Transmission; China

Mingming Cai

Emerging transportation technologies, shared mobility and land use, interaction between human mobility based on shared vehicles and urban land uses. Spatio-temporal analysis and big data. Smart visualization methods