What can U.S. Travel Data tell Planners about Opening the Economy during COVID-19?
Manish Shirgaokar (email@example.com), University of Colorado, DenverShow Abstract
Aditi Misra, University of Michigan
Erin Nobler, University of Colorado, Denver
Diana Muresan, University of Colorado, Denver
As the COVID-19 pandemic rages on creating chaos on the public health and economic fronts, there has been an active debate about whether to shelter in place or open the economy. Health experts agree that until scalable medical solutions are available, policymakers should follow a shelter-in-place approach. However, such a policy may have unequal impacts on locations with different socio-demographic and economic makeup. Additionally, planners may be asked to implement local policies to open the economy by elected officials. In this paper, we rely on the Google Mobility panel, reported at the county level for the U.S., which shows how travel patterns shifted across various trip types compared to a pre-pandemic baseline. This data reveals where travel was occurring. We joined U.S. County-level data for socio-demographics, economic indicators, COVID-19 caseload, and votes by political party to the mobility information. We estimated three sets of nested linear mixed effects models, one each for grocery/pharmacy, retail/recreation, and public transportation trips. U.S. counties having higher percentages of African-Americans and a combination of more rental housing plus higher median income saw increased travel. Planners for such counties need to be aware of the nature of travel in these locations. Though policies to limit the spread of the disease are necessary, planners need to understand better the nature of travel, discretionary versus essential, and have policies in place to reduce the former while supporting the latter with appropriate safety mechanisms.
Mobility Patterns and the Spread of COVID-19 in Latin America: The Case of Santiago de Chile
Francisca Giraldez (firstname.lastname@example.org), Inter-American Development BankShow Abstract
Felipe Bedoya-Maya, Inter-American Development Bank
Agustina Calatayud, Inter-American Development Bank
Santiago Sanchez-Gonzalez, Inter-American Development Bank
Despite Latin America being the current epicenter of the COVID-19 pandemic, there is still little evidence on the relationship between mobility and virus propagation in the region. To fill in this gap, this paper combines network analysis of mobility patterns with a spatial error correction model for Santiago de Chile, finding that a 10% increase in the number of public transportation trips received by an administrative unit is associated with a 1.3% growth in the rate of confirmed COVID-19 cases per 100,000 inhabitants. Based on these findings, we proposed an empirical method to identify and classify neighborhoods according to the level of risk for COVID-19 propagation, which both can assist policymakers’ in managing mobility while a vaccine is developed.
Mobility Adaptation Disparity among Income Groups during the COVID-19 Pandemic
Kentaro Iio (email@example.com), Traf-IQ, Inc.Show Abstract
Xiaoyu "Sky" Guo, Texas A&M University, College Station
Xiaoqiang Kong, Texas A&M University, College Station
Kelly Rees, N/A
Bruce Wang, Texas A&M University, College Station
The coronavirus disease 2019 (COVID-19) pandemic has severely impacted health and economic conditions worldwide. In response, governments have imposed orders upon or encouraged citizens to stay home to slow down the spread of the virus. Current literature from the United States infers that only limited socioeconomic classes provide people with the ability to practice remote work, but there has been little research on mobility disparity in US cities. We tried to fill this gap by quantifying the impacts of the pandemic on human mobility by income class in Houston-The Woodlands-Sugar Land, Texas. Using pseudonymized cell phone data of 10,388 people, we performed a longitudinal study on mobility as measured by the total travel length, the radius of gyration, and the number of visited locations in April 2020 compared to the data in January and February 2020. We found an apparent disparity in mobility. In particular, there was a strong negative correlation (ρ = -0.98) between the estimated income class of a traveler and the travel length in April. Furthermore, larger percentage drops among higher-income classes in the radius of gyration and number of visited locations implied different adaptability in mobility. Nevertheless, the findings of this study suggest a need to understand the reasons behind the mobility inflexibility among low-income populations during the unprecedented global and health and economic crisis.
Modeling public transport recovery time following the COVID-19 pandemic outbreak: Evidence from Athens, Greece
Athanasios Kopsidas, National Technical University of Athens (NTUA)Show Abstract
Christina Milioti, University of West Attica
Konstantinos Kepaptsoglou, National Technical University of Athens (NTUA)
Eleni Vlahogianni, National Technical University of Athens (NTUA)
The COVID-19 outbreak led to significant changes in daily commuting. As lockdowns were imposed to metropolitan areas throughout the globe, travelers refrained heavily from using public transport, to maintain social distancing. Based on data from Athens, Greece, this paper investigates the anticipated, post-pandemic behavior of travelers with respect to using public transport. Focus is given on analyzing those factors that affect port-pandemic recovery time of public transport users, i.e. the time travelers would refrain from using public transport, following a gradual exit from the pandemic outbreak and relaxation of lockdowns. A discrete duration model is developed for that purpose. Findings suggest that self-employed, middle aged and travelers who mostly use private vehicles, are less likely to use public transport after the outbreak. When it comes to psychological factors and travelers’ perception, those who would be willing to use protection gear when traveling with public transport are also less likely to return to this way of commuting.
Impact of COVID-19 on Food Shopping: A Spatio-Temporal Analysis of Changes in Travel to Supermarket and Grocery Stores
Armita Kar (firstname.lastname@example.org), Ohio State UniversityShow Abstract
Huyen Le, Ohio State University
Andre Carrel, Ohio State University
Yasuyuki Motoyama, Ohio State University
Harvey Miller, Ohio State University
This study evaluates the impacts of the COVID-19 pandemic on food shopping travel patterns. We examined the recovery patterns of various food retailers by size and characteristics (e.g., local stores, dollar stores, mid/high-end, and big-box grocery stores). We applied visualization and mapping techniques to illustrate the spatio-temporal changes in store visits and traffic flows during the lockdown and initial reopening phase of COVID-19. We also developed two hurdle models to identify the key socio-economic and built environment determinants of the store traffic changes. The results show that at the aggregate level, all types of food retailers experienced a decline in their average weekly traffic during the lockdown phase. Also, the average decline in weekly store traffic has decreased from the lockdown phase to the reopening phase. At the store-specific level, the rate of decrease between these two phases is lower for local stores and dollar stores compared to the mid/high-end end and big-box grocery stores. Specially, local stores located in clusters with other mid/high-end grocery stores are experiencing a slower recovery in store traffic during the initial reopening phase of COVID-19. We also found that the local stores in the food desert regions had a lesser decline in store traffic, indicating the dependency of local residents on these stores. Findings from this study will help the practitioners and policymakers understand the most impacted food stores with their spatial locations and develop strategies for their economic revival.
Spatial Accessibility Assessment of COVID-19 Patients to Healthcare Facilities: A Case Study of Florida
Mahyar Ghorbanzadeh (email@example.com), Florida A&M University-Florida State University College of EngineeringShow Abstract
Kyusik Kim, Florida State University
Eren Ozguven, Florida A&M University-Florida State University College of Engineering
Mark Horner, Florida State University
During the COVID-19 pandemic, healthcare facilities all over the world were overwhelmed by the amount of coronavirus patients needed to be served. Similarly, the U.S. also experienced a shortage of healthcare resources, which led to a reduction in the efficiency of the whole healthcare system. In order to evaluate this from a transportation perspective, it is critical to understand the extent to which healthcare facilities with ICU beds are available in both urban and rural areas. As such, this study aims to assess the spatial accessibility of COVID-19 patients to the healthcare facilities in the State of Florida. For this purpose, two methods were used: the two-step floating catchment area (2SFCA) and the enhanced two-step floating catchment area (E2SFCA). These methods were applied to identify the high and low access areas in the entire state. Furthermore, a metric namely, the Accessibility Ratio Difference (ARD), was developed to evaluate the spatial access difference between the models. Results revealed that many areas in the northwest and southern Florida have lower access compared to other locations. The residents in central Florida (e.g., Tampa and Orlando cities) had the highest level of accessibility given the high access ratios. We also observed that the 2SFCA method overestimates the accessibility in the areas with a lower number of ICU beds due to “equal access” assumption of the population within the catchment area. Findings of this study can provide valuable insights and information for the state officials and decision makers in the field of public health.
Compact Development and Adherence to Social Distancing During the COVID-19 Pandemic: A Longitudinal Investigation in the United States
Shima Hamidi (firstname.lastname@example.org), Johns Hopkins UniversityShow Abstract
Ahoura Zandiatashbar, San Jose State University
In the absence of a vaccine and medical treatments, social distancing remains the only option available to governments in order to slow the spread of global pandemics such as COVID-19 and save millions of lives. Despite the scientific evidence on the effectiveness of social distancing measures, they are not being practiced uniformly across the U.S. Accordingly, the role of compact development on the level of adherence to social distancing measures has not been empirically studied. This longitudinal study employs a natural experimental research design to investigative the impacts of compact development on reduction in travel to three types of destinations representing a range of essential and non-essential trips in 771 metropolitan counties in the U.S. during the shelter-in-place order amid the COVID-19 pandemic. We employed Multilevel Linear Modeling (MLM) for the three longitudinal analyses in this study to model determinants of reduction in daily trips to grocery stores, parks, and transit stations; using travel data from Google and accounting for the hierarchical (two-level) structure of the data. We found that the challenges of practicing social distancing in compact areas are not related to minimizing essential trips. Quite the opposite, residents of compact areas have significantly higher reduction in trips to essential destinations such as grocery stores/pharmacies, and transit stations. However, residents of compact counties have significantly lower reduction in their trips to parks possibly due to the smaller homes, lack of private yards, and the higher level of anxiety amid the pandemic.
Public Transport Demand and Supply Changes During COVID-19 Pandemic: The Case of the city of São Paulo, Brazil
Aitan Militao, No OrganizationShow Abstract
Igor Maranhão, Universidade Federal do Rio de Janeiro
Romulo Orrico, Alberto Luiz Coimbra Institute for Graduate Studies and Research in Engineering (COPPE/UFRJ)
Public transportation has faced a decline in ridership worldwide during the COVID-19 pandemic. Although transit authorities tried to adapt the service supply, the inherent disparities between countries influence the different responses from the population, and the resultant impacts on the different social groups. Under this perspective, cities in developing countries face a challenge related not only to the reduction in demand and revenue in the public transport sector, but also the implications on the social tissue and in the existing inequalities. This paper analyzes the change in demand and supply of public transportation in the city of São Paulo, Brazil, during the COVID-19 pandemic, taking into consideration the inherent local social inequalities of the city. The results show that the reduction in demand is not equally proportional to different passenger types and social groups, and suggests that the specific car restriction measure adopted might have helped to increase public transport demand during the pandemic, in a period of reduced supply. The analysis of changes in supply and demand per transit line type shows that although reductions were performed equally, the realized demand reduction is lower on lines connecting the peripheral areas to the city center. Lastly, Getis-Ord spatial statistics were implemented to identify areas of significant clusters of high and low values of bus supply change and COVID-19 cases, the results showed that 0.91% of the areas are simultaneously bus supply change cold spots and COVID-19 hot spots.
Healthcare and Pharmacy Access Challenges Among Former Transit Riders During COVID-19 Lockdowns in Toronto and Vancouver
Matthew Palm (email@example.com), University of Toronto, ScarboroughShow Abstract
Shelby Sturrock, University of Toronto
Nicholas Howell, University of Toronto
Michael Widener, University of Toronto
Steven Farber, University of Toronto, Scarborough
Most public transit users across North America stopped using public transit when COVID-19 related lockdowns began in March of 2020. We surveyed over 4,000 former public transit riders in Toronto and Vancouver, Canada, to understand how giving up transit impacted their ability to access healthcare during lockdown. Specifically, we asked former transit riders whether giving up public transit made it harder for them to access healthcare or get prescriptions. We also asked whether they put off or postponed any medical appointments until they could use public transit again. We analyzed these data using robust Poisson models estimated using quasi-ML (quasiPoisson). Results suggest that males and people living in walkable neighborhoods where it was easy to maintain physical distancing were less likely to have trouble accessing healthcare and prescriptions after giving up public transit. In contrast, non-white former transit riders, recent immigrants, people with disabilities, those who did not own or have access to a vehicle, people with poor health were more likely to report that giving up public transit made it harder to access healthcare and get prescriptions. These groups were also more likely to report putting off or rescheduling medical appointments until they could use transit again. We conclude that efforts to promote local walkability, as well as efforts to provide improved local and/or virtual access to healthcare and pharmacies, are urgently needed during pandemics and other major events when transit-reliant urban residents may be unable to use public transit.
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