Is travel behaviour an equity issue? Using GPS location data to assess the effects of income and supermarket availability on travel reduction during the COVID-19 pandemic

References

• Abdullah, M., Dias, C., Muley, D., & Shahin, M. (2020). Exploring the impacts of COVID-19 on travel behavior and mode preferences. Transportation Research Interdisciplinary Perspectives, 8, 100255. doi:10.1016/j.trip.2020.100255
   PubMedGoogle Scholar
• Almagro, M., & Orane-Hutchinson, A. (2020). JUE Insight: the determinants of the differential exposure to COVID-19 in New York City and their evolution over time. Journal of Urban Economics, 103293. doi:10.1016/j.jue.2020.103293
   PubMed Web of Science ®Google Scholar
• Alon, T., Doepke, M., Olmstead-Rumsey, J., & Tertilt, M. (2020). This time it’s different: The role of women’s employment in a pandemic recession (No. w27660). National Bureau of Economic Research. doi:10.3386/w27660
   Google Scholar
• Anselin, L. (1988). Spatial econometrics: Methods and models. Dordrecht: Kluwer.
   Google Scholar
• Anselin, L., Syabri, I., & Kho, Y. (2010). Geoda: An introduction to spatial data analysis. In Fischer M., Getis A. (eds) Handbook of applied spatial analysis (pp. 73–89). Berlin, Heidelberg: Springer.
   Google Scholar
• Baena-Díez, J., Barroso, M., Cordeiro-Coelho, S., Díaz, J., & Grau, M. (2020). Impact of COVID-19 outbreak by income: Hitting hardest the most deprived. Journal of Public Health, 42(4), 698–703. doi:10.1093/pubmed/fdaa136
   PubMed Web of Science ®Google Scholar
• Bower, K. M., Thorpe, R. J., Rohde, C., & Gaskin, D. J. (2014). The intersection of neighborhood racial segregation, poverty, and urbanicity and its impact on food store availability in the United States. Preventive Medicine, 58, 33–39. doi:10.1016/j.ypmed.2013.10.010
   PubMed Web of Science ®Google Scholar
• Brinkman, P., & Mangum, K. (2020). The geography of travel behavior during the early phase of the Covid-19 pandemic. Federal Reserve Bank of Philadelphia. doi:10.21799/frbp.wp.2020.38
   Google Scholar
• Brough, R., Freedman, M., & Phillips, D. C. (2020). Understanding socioeconomic disparities in travel behavior during the COVID-19 pandemic. In Working Papers (No. 192007; Working Papers). University of California-Irvine, Department of Economics. https://ideas.repec.org/p/irv/wpaper/192007.html
   Google Scholar
• Chang, S., Pierson, E., Koh, P. W., Gerardin, J., Redbird, B., Grusky, D., & Leskovec, J. (2021). Mobility network models of COVID-19 explain inequities and inform reopening. Nature, 589(7840), 82–87. doi:10.1038/s41586-020-2923-3
   PubMed Web of Science ®Google Scholar
• Circella, G., & Dominguez-Faus, R. (2020). Impacts of the COVID-19 pandemic on transportation use: Updates from UC Davis behavioral study. UC Davis Institute of Transportation Studies. https://its.ucdavis.edu/blog-post/impacts-of-the-covid-19-pandemic-on-transportation-use-updates-from-uc-davis-behavioral-study/
   Google Scholar
• Couch, K. A., Fairlie, R. W., & Xu, H. (2020). Early evidence of the impacts of COVID-19 on minority unemployment. Journal of Public Economics, 192, 104287. doi:10.1016/j.jpubeco.2020.104287
   PubMed Web of Science ®Google Scholar
• The COVID Tracking Project. (2020). The COVID racial data tracker. The COVID tracking project at the Atlantic. https://covidtracking.com/race
   Google Scholar
• Craig, J. (1984). Averaging population density. Demography, 21(3), 405–412.
   PubMed Web of Science ®Google Scholar
• Dave, D., Friedson, A., Matsuzawa, K., Sabia, J., & Safford, S. (2020). JUE Insight: were urban cowboys enough to control COVID-19? Local shelter-in-place orders and coronavirus case growth. Journal of Urban Economics, 2020, 103294. doi:10.1016/j.jue.2020.103294
   Google Scholar
• De Vos, J. (2020). The effect of COVID-19 and subsequent social distancing on travel behavior. Transportation Research Interdisciplinary Perspectives, 5, 100121. doi:10.1016/j.trip.2020.100121
   PubMedGoogle Scholar
• Dingel, J. I., & Neiman, B. (2020). How many jobs can be done at home? Journal of Public Economics, 189, 104235. doi:10.1016/j.jpubeco.2020.104235
   PubMed Web of Science ®Google Scholar
• Dutko, P., Ploeg, M. V., & Farrigan, T. (2012). Characteristics and influential factors of food deserts (No. 140; Economic Research report, p. 36). United States Department of Agriculture. https://www.ers.usda.gov/webdocs/publications/45014/30940_err140.pdf
   Google Scholar
• Engle, S., Stromme, J., & Zhou, A. (2020). Staying at home: Mobility effects of COVID-19 [Working Paper]. https://doi.org/10.2139/ssrn.3565703
   Google Scholar
• Figliozzi, M., & Keeling, K. (2019, October 15). E-Grocery home delivery impacts on food distribution, access and equity: A portland case study. International Urban Freight Conference, Long Beach, CA. https://pdxscholar.library.pdx.edu/cengin_fac/544
   Google Scholar
• Fraiberger, S., Astudillo, P., Candeago, L., Chunet, A., Jones, N., Khan, M., … Montfort, A. (2020). Uncovering socioeconomic gaps in mobility reduction during the COVID-19 pandemic using location data. arXiv:2006.15195 [COVID-19 e-print]. https://arxiv.org/abs/2006.15195
   Google Scholar
• Frith, J., & Saker, M. (2020). It is all about location: Smartphones and tracking the spread of COVID-19. Social Media + Society, 6, 3. doi:10.1177%2F2056305120948257
   Google Scholar
• Gao, S., Rao, J., Kang, Y., Liang, Y., Kruse, J., Dopfer, D., … Patz, J. (2020). Association of mobile phone location data indications of travel and stay-at-home mandates with COVID-19 infection rates in the US. Jama Network Open, 3(9), e2020485. http://jamanetwork.com/article.aspx?doi=10.1001/jamanetworkopen.2020.20485
   PubMed Web of Science ®Google Scholar
• Gezici, A., & Ozay, O. (2020). How race and gender shape COVID-19 unemployment probability (Working Paper ID 3675022). Social Science Research Network. https://doi.org/10.2139/ssrn.3675022
   Google Scholar
• Ghosh, A., Nundy, S., Ghosh, S., & Mallick, T. (2020). Study of COVID-19 pandemic in London (UK) from urban context. Cities, 106, 102928. doi:10.1016/j.cities.2020.102928
   PubMed Web of Science ®Google Scholar
• Gittelsohn, J., Franceschini, M. C. T., Rassoly, I. R., Ries, A. V., Ho, L. S., Pavlovich, W., … Frick, K. D. (2008). Understanding the food environment in a low-income urban setting: Implications for food store interventions. Journal of Hunger & Environmental Nutrition, 2(2–3), 33–50. doi:10.1080/19320240801891438
   Google Scholar
• Glaeser, E., Gorback, C., & Redding, S. (2020). JUE Insight: how much does COVID-19 increase with mobility? Evidence from New York and four other U.S. Cities. Journal of Urban Economics, 103292. doi:10.1016/j.jue.2020.103292
   Google Scholar
• Gong, L., Morikawa, T., Yamamoto, T., & Sato, H. (2014). Deriving personal trip data from GPS data: A literature review on the existing methodologies. Procedia - Social and Behavioral Sciences, 138, 557–565. doi:10.1016/j.sbspro.2014.07.239
   Google Scholar
• Grashuis, J., Skevas, T., & Segovia, M. (2020). Grocery shopping preferences during the COVID-19 pandemic. Sustainability, 12(13), 5369. doi:10.3390/su12135369
   Web of Science ®Google Scholar
• Hamidi, S., Sabouri, S., & Ewing, R. (2020). Does density aggravate the COVID-19 pandemic? Journal of the American Planning Association, 86(4), 495–509. doi:10.1080/01944363.2020.1777891
   Web of Science ®Google Scholar
• Hara, Y., & Yamaguchi, H. (2021). Japanese travel behavior trends and change under COVID-19 state-of-emergency declaration: Nationwide observation by mobile phone location data. Transportation Research Interdisciplinary Perspectives, 9, 100288. doi:10.1016/j.trip.2020.100288
   PubMedGoogle Scholar
• Heroy, S., Loaiza, I., Pentland, A., & O’Clery, N. (2020). Controlling COVID-19: Labor structure is more important than lockdown policy. arXiv:2010.14630. https://arxiv.org/abs/2010.14630
   Google Scholar
• Hillier, A., Cannuscio, C. C., Karpyn, A., McLaughlin, J., Chilton, M., & Glanz, K. (2011). How far do low-income parents travel to shop for food? Empirical evidence from two urban neighborhoods. Urban Geography, 32(5), 712–729. doi:10.2747/0272-3638.32.5.712
   Web of Science ®Google Scholar
• Iio, K., Guo, X., “Jack” Kong, X., Rees, K., & Wang, X. B. (2020). COVID-19 and social distancing: Disparities in mobility adaptation by income. arXiv:2011.12510. [COVID-19 e-print]. https://arxiv.org/abs/2011.12510
   Google Scholar
• Jin, X., & Wu, J. (2011). Propensity to telecommute: Exploring the national household travel survey. Transportation Research Record, 2231(1), 110–119. doi:10.3141/2231-14
   Google Scholar
• Jones, J. H., & Salathé, M. (2009). Early assessment of anxiety and behavioral response to novel swine-origin influenza A(H1N1). PloS One, 4(12), e8032. doi:10.1371/journal.pone.0008032
   PubMed Web of Science ®Google Scholar
• Liu, L. (2020). Emerging study on the transmission of the novel coronavirus (COVID-19) from urban perspective: Evidence from China. Cities, 103, 102759. doi:10.1016/j.cities.2020.102759
   PubMed Web of Science ®Google Scholar
• Maroko, A. R., Nash, D., & Pavilonis, B. T. (2020). COVID-19 and inequity: A comparative spatial analysis of New York city and Chicago hot spots. Journal of Urban Health, 97(4), 461–470. doi:10.1007/s11524-020-00468-0
   PubMed Web of Science ®Google Scholar
• Maryland Transportation Institute. (2020). University of Maryland COVID-19 impact analysis platform. College Park: University of Maryland. https://data.covid.umd.edu, Accessed on Dec. 24. 2020
   Google Scholar
• Mattson, J. W. (2012). Travel behavior and mobility of transportation-disadvantaged populations: Evidence from the National Household Travel Survey (DP-258). North Dakota State University, Fargo: Upper Great Plains Transportation Institute.
   Google Scholar
• Molloy, J., Tchervenkov, C., Hintermann, B., & Axhausen, K. (2020). Tracing the Sars-CoV-2 impact: The first month in Switzerland. Transport Findings, May. https://doi.org/10.32866/001c.12903
   Google Scholar
• Moore, S. E., Jones-Eversley, S. D., Tolliver, W. F., Wilson, B. L., & Jones, C. A. (2020). Six feet apart or six feet under: The impact of COVID-19 on the Black community. Death Studies, 1–11. doi:10.1080/07481187.2020.1785053
   Web of Science ®Google Scholar
• Ooms, J. (2014). The jsonlite package: A practical and consistent mapping between JSON Data and R objects. arXiv:1403.2805 [stat.CO] URL https://arxiv.org/abs/1403.2805
   Google Scholar
• Park, J. (2021). Who Is hardest hit by a pandemic? Racial disparities in COVID-19 hardship in the U.S. International Journal of Urban Sciences, doi:10.1080/12265934.2021.1877566
   Web of Science ®Google Scholar
• Powell, L. M., Slater, S., Mirtcheva, D., Bao, Y., & Chaloupka, F. J. (2007). Food store availability and neighborhood characteristics in the United States. Preventive Medicine, 44(3), 189–195. doi:10.1016/j.ypmed.2006.08.008
   PubMed Web of Science ®Google Scholar
• Pullano, G., Valdano, E., Scarpa, N., Rubrichi, S., & Colizza, V. (2020). Evaluating the effect of demographic factors, socioeconomic factors, and risk aversion on mobility during the COVID-19 epidemic in France under lockdown: A population-based study. The Lancet Digital Health, 2(12), e638–e649. doi:10.1016/S2589-7500(20)30243-0
   PubMedGoogle Scholar
• Raine, S., Liu, A., Mintz, J., Wahood, W., Huntley, K., & Haffizulla, F. (2020). Racial and ethnic disparities in covid-19 outcomes: Social determination of health. International Journal of Environmental Research and Public Health, 17(21), 8115. doi:10.3390/ijerph17218115
   PubMed Web of Science ®Google Scholar
• Sen-Crowe, B., McKenney, M., & Elkbuli, A. (2020). Social distancing during the COVID-19 pandemic: Staying home save lives. The American Journal of Emergency Medicine, 38(7), 1519–1520. doi:10.1016/j.ajem.2020.03.063
   PubMed Web of Science ®Google Scholar
• Sevilla, A., & Smith, S. (2020). Baby steps: The gender division of childcare during the COVID-19 pandemic. Oxford Review of Economic Policy, 36(Supplement_1), S169–S186. doi:10.1093/oxrep/graa027
   Web of Science ®Google Scholar
• Shakibaei, S., De Jong, G., Alpkökin, P., & Rashidi, T. (2020). Impact of the COVID-19 pandemic on travel behavior in Istanbul: A panel data analysis. Sustainable Cities and Society, 65, 102619. doi:10.1016/j.scs.2020.102619
   PubMed Web of Science ®Google Scholar
• Shamshiripour, A., Rahimi, E., Shabanpour, R., & Mohammadian, A. (2020). How is COVID-19 reshaping activity-travel behavior? Evidence from a comprehensive survey in Chicago. Transportation Research Interdisciplinary Perspectives, 7, 100216. doi:10.1016/j.trip.2020.100216
   PubMedGoogle Scholar
• Spurlock, C. A., Todd-Blick, A., Wong-Parodi, G., & Walker, V. (2020). Children, income, and the impact of home delivery on household shopping trips. Transportation Research Record, 2674(10), 335–350. doi:10.1177/0361198120935113
   Web of Science ®Google Scholar
• Teixeira da Silva, J. A., Tsigaris, P., & Erfanmanesh, M. (2020). Publishing volumes in major databases related to Covid-19. Scientometrics, doi:10.1007/s11192-020-03675-3
   PubMed Web of Science ®Google Scholar
• Ulfarsson, G. F., Steinbrenner, A., Valsson, T., & Kim, S. (2015). Urban household travel behavior in a time of economic crisis: Changes in trip making and transit importance. Journal of Transport Geography, 49, 68–75. doi:10.1016/j.jtrangeo.2015.10.012
   Web of Science ®Google Scholar
• Unnikrishnan, A., & Figliozzi, M. (2020). A study of the impact of COVID-19 on home delivery purchases and expenditures [Working Paper]. https://pdxscholar.library.pdx.edu/cengin_fac/557
   Google Scholar
• van Dorn, A., Cooney, R. E., & Sabin, M. L. (2020). COVID-19 exacerbating inequalities in the US. Lancet (London, England), 395(10232), 1243–1244. doi:10.1016/S0140-6736(20)30893-X
   PubMed Web of Science ®Google Scholar
• Walker, R. E., Keane, C. R., & Burke, J. G. (2010). Disparities and access to healthy food in the United States: A review of food deserts literature. Health & Place, 16(5), 876–884. doi:10.1016/j.healthplace.2010.04.013
   PubMed Web of Science ®Google Scholar
• Warren, M., & Skillman, S. (2020). Mobility changes in response to COVID-19, arXiv:2003.14228. [COVID-19 e-print]. https://arxiv.org/abs/2003.14228
   Google Scholar
• Wickham, H. (2020). httr: Tools for Working with URLs and HTTP. R package version 1.4.2. https://CRAN.R-project.org/package=httr
   Google Scholar
• Wright, A. L., Sonin, K., Driscoll, J., & Wilson, J. (2020). Poverty and economic dislocation reduce compliance with COVID-19 shelter-in-place protocols (SSRN Scholarly Paper ID 3573637). Social Science Research Network. https://doi.org/10.2139/ssrn.3573637
   Google Scholar
• Xiong, C., Hu, S., Yang, M., Younes, H., Luo, W., Ghader, S., & Zhang, L. (2020). Mobile device location data reveal human mobility response to state-level stay-at-home orders during the COVID-19 pandemic in the USA. Journal of the Royal Society Interface, 1720200344. doi:10.1098/rsif.2020.0344
   Web of Science ®Google Scholar
• Zhang L, Ghader S, Pack M, Darzi A, Xiong C, Yang M, Sun Q, Kabiri A, Hu S. (2020). An interactive COVID-19 mobility impact and social distancing analysis platform. medRxiv 2020. https://doi.org/10.1101/2020.04.29.20085472 (preprint)
   Google Scholar
• Zumbrun, J. (2020, May 10). Coronavirus slump is worst since great depression. Will it be as painful? Wall Street Journal. https://www.wsj.com/articles/coronavirus-slump-is-worst-since-great-depression-will-it-be-as-painful-11589115601
   Google Scholar