The characteristics of multi-source mobility datasets and how they reveal the luxury nature of social distancing in the U.S. during the COVID-19 pandemic

References

• Almagro, M., and A. Orane-Hutchinson. 2020. “The Determinants of the Differential Exposure to COVID-19 in New York City and Their Evolution Over Time.” Covid Economics: Vetted and Real-Time Papers, (13).
   Google Scholar
• Apple Mobility Trends Reports. 2020. Accessed July 8, 2020. https://www.apple.com/covid19/mobility.
   Google Scholar
• Barnett-Howell, Z., and A. M. Mobarak. 2020. “The Benefits and Costs of Social Distancing in Rich and Poor Countries.” arXiv:2004.04867.
   Google Scholar
• Block, J. P., R. A. Scribner, and K. B. DeSalvo. 2004. “Fast Food, Race/Ethnicity, and Income: A Geographic Analysis.” American Journal of Preventive Medicine 27 (3): 211–217.
   PubMed Web of Science ®Google Scholar
• Breteler, J. K., J. S. Tam, M. Jit, J. C. Ket, and M. R. De Boer. 2013. “Efficacy and Effectiveness of Seasonal and Pandemic A (H1N1) 2009 Influenza Vaccines in low and Middle Income Countries: A Systematic Review and Meta-Analysis.” Vaccine 31 (45): 5168–5177.
   PubMed Web of Science ®Google Scholar
• Buckee, C. O., S. Balsari, J. Chan, M. Crosas, F. Dominici, U. Gasser, and M. Lipsitch. 2020. “Aggregated Mobility Data Could Help Fight COVID-19.” Science (New York, NY) 368 (6487): 145.
   Google Scholar
• Chiou, L., and C. E. Tucker. 2020. “Social Distancing, Internet Access and Inequality.” NBER Working Paper, w26982.
   Google Scholar
• Cooper, R. S. 2001. “Social Inequality, Ethnicity and Cardiovascular Disease.” International Journal of Epidemiology 30 (Suppl._1): S48.
   PubMedGoogle Scholar
• Coven, J., and A. Gupta. 2020. “Disparities in Mobility Responses to Covid-19.” NYU Stern Working Paper.
   Google Scholar
• Cui, Y., X. Xie, and Y. Liu. 2018. “Social Media and Mobility Landscape: Uncovering Spatial Patterns of Urban Human Mobility with Multi Source Data.” Frontiers of Environmental Science & Engineering 12 (5): 7.
   Web of Science ®Google Scholar
• Fauver, J. R., M. E. Petrone, E. B. Hodcroft, K. Shioda, H. Y. Ehrlich, A. G. Watts, C. B. F. Vogels, et al 2020. “Coast-to-Coast Spread of SARS-CoV-2 During the Early Epidemic in the United States.” Cell 181 (5): 990–996.e5. doi:10.1016/j.cell.2020.04.021.
   PubMed Web of Science ®Google Scholar
• Fotheringham, A. S., and D. W. Wong. 1991. “The Modifiable Areal Unit Problem in Multivariate Statistical Analysis.” Environment and Planning A 23 (7): 1025–1104.
   Web of Science ®Google Scholar
• Gatto, M., E. Bertuzzo, L. Mari, S. Miccoli, L. Carraro, R. Casagrandi, and A. Rinaldo. 2020. “Spread and Dynamics of the COVID-19 Epidemic in Italy: Effects of Emergency Containment Measures.” Proceedings of the National Academy of Sciences 117 (19): 10484–10491.
   PubMed Web of Science ®Google Scholar
• Gaziano, T. A., A. Bitton, S. Anand, S. Abrahams-Gessel, and A. Murphy. 2010. “Growing Epidemic of Coronary Heart Disease in Low-and Middle-Income Countries.” Current Problems in Cardiology 35 (2): 72–115.
   PubMed Web of Science ®Google Scholar
• Gonzalez, M. C., C. A. Hidalgo, and A. L. Barabasi. 2008. “Understanding Individual Human Mobility Patterns.” Nature 453 (7196): 779–782.
   PubMed Web of Science ®Google Scholar
• Google Community Mobility Reports. 2020. Accessed July 8, 2020. https://www.google.com/covid19/mobility/.
   Google Scholar
• Greenough, J. 2014, September 3. “The Median Income For iPhone Users Is 40% Higher Than That Of Android Users.” Accessed July 20, 2020. https://www.businessinsider.com/the-median-income-for-iphone-users-is-40-higher-than-that-of-android-users-2014-9.
   Google Scholar
• Hoover, G. A., R. A. Compton, and D. C. Giedeman. 2015. “The Impact of Economic Freedom on the Black/White Income Gap.” American Economic Review 105 (5): 587–592.
   Web of Science ®Google Scholar
• Huang, X., Z. Li, Y. Jiang, X. Li, and D. Porter. 2020a. “Twitter Reveals Human Mobility Dynamics During the COVID-19 Pandemic.” PLoS ONE 15 (11): e0241957.
   PubMed Web of Science ®Google Scholar
• Huang, X., Z. Li, J. Lu, S. Wang, H. Wei, and B. Chen. 2020b. “Time-series Clustering for Home Dwell Time During COVID-19: What Can we Learn from it?” ISPRS International Journal of Geo-Information 9 (11): 675.
   Web of Science ®Google Scholar
• Huang, X., C. Wang, and Z. Li. 2018. “Reconstructing Flood Inundation Probability by Enhancing Near Real-Time Imagery with Real-Time Gauges and Tweets.” IEEE Transactions on Geoscience and Remote Sensing 56 (8): 4691–4701.
   Web of Science ®Google Scholar
• Jawaid, A. 2020. “Protecting Older Adults During Social Distancing.” Science 368 (6487): 145.
   PubMed Web of Science ®Google Scholar
• Jiang, Y., Z. Li, and X. Ye. 2019. “Understanding Demographic and Socioeconomic Biases of Geotagged Twitter Users at the County Level.” Cartography and Geographic Information Science 46 (3): 228–242.
   Web of Science ®Google Scholar
• Jones, B. 2020, May 31. “Urban Residents in States Hit Hard by COVID-19 Most Likely to See it as a Threat to Daily Life.” Accessed July 24, 2020. https://www.pewresearch.org/fact-tank/2020/03/20/urban-residents-in-states-hit-hard-by-covid-19-most-likely-to-see-it-as-a-threat-to-daily-life/.
   Google Scholar
• Kraemer, M. U., C. H. Yang, B. Gutierrez, C. H. Wu, B. Klein, D. M. Pigott, and J. S. Brownstein. 2020. “The Effect of Human Mobility and Control Measures on the COVID-19 Epidemic in China.” Science 368 (6490): 493–497.
   PubMed Web of Science ®Google Scholar
• Lau, B. P. L., S. H. Marakkalage, Y. Zhou, N. U. Hassan, C. Yuen, M. Zhang, and U. X. Tan. 2019. “A Survey of Data Fusion in Smart City Applications.” Information Fusion 52: 357–374.
   Web of Science ®Google Scholar
• Li, Z., X. Huang, X. Ye, and X. Li. 2020. “ODT Flow Explorer: Extract, Query, and Visualize Human Mobility.” arXiv preprint arXiv:2011.12958.
   Google Scholar
• Lou, J., X. Shen, and D. Niemeier. 2020. “Are Stay-at-Home Orders More Difficult to Follow for Low-Income Groups?” Journal of Transport Geography 89: 102894.
   PubMed Web of Science ®Google Scholar
• Martín, Y., S. Cutter, and Z. Li. 2019. “ Bridging Social Media and Survey Data for the Evacuation Assessment of Hurricanes.” Natural Hazard Review 21 (2): 04020003.
   Web of Science ®Google Scholar
• McKenzie, B. 2013. “County-to-County Commuting Flows: 2006-10.” US Census Bureau.
   Google Scholar
• Montero, L., X. Ros-Roca, R. Herranz, and J. Barceló. 2019. “Fusing Mobile Phone Data with Other Data Sources to Generate Input OD Matrices for Transport Models.” Transportation Research Procedia 37: 417–424.
   Google Scholar
• Muennig, P., P. Franks, H. Jia, E. Lubetkin, and M. R. Gold. 2005. “The Income-Associated Burden of Disease in the United States.” Social Science & Medicine 61 (9): 2018–2026.
   PubMed Web of Science ®Google Scholar
• Nayak, A., S. J. Islam, A. Mehta, Y. A. Ko, S. A. Patel, A. Goyal, S. A. Sullivan, et al. 2020. “Impact of Social Vulnerability on COVID-19 Incidence and Outcomes in the United States.” medRxiv. doi:10.1101/2020.04.10.20060962.
   Google Scholar
• Nguyen, V. K., and K. Peschard. 2003. “Anthropology, Inequality, and Disease: A Review.” Annual Review of Anthropology 32 (1): 447–474.
   Google Scholar
• Oliver, N., E. Letouzé, H. Sterly, S. Delataille, M. De Nadai, B. Lepri, and R. Lambiotte. 2020. “Mobile Phone Data and COVID-19: Missing an Opportunity?” arXiv preprint arXiv:2003.12347.
   Google Scholar
• Qiu, J., B. Shen, M. Zhao, Z. Wang, B. Xie, and Y. Xu. 2020. “A Nationwide Survey of Psychological Distress among Chinese People in the COVID-19 Epidemic: Implications and Policy Recommendations.” General Psychiatry 33 (2): e100213.
   PubMed Web of Science ®Google Scholar
• Roberts, S., M. Osborne, M. Ebden, S. Reece, N. Gibson, and S. Aigrain. 2013. “Gaussian Processes for Time-Series Modelling.” Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 371 (1984): 20110550.
   PubMed Web of Science ®Google Scholar
• Scott, M., L. Cerulus, and L. Kayali. 2020. “European Commission Tells Carriers to Hand Over Mobile Data in Coronavirus Fight.” Accessed June 8, 2020. https://www.politico.com/news/2020/03/24/europe-mobile-data-coronavirus-146074.
   Google Scholar
• Siddharthan, T., M. R. Grigsby, D. Goodman, M. Chowdhury, A. Rubinstein, V. Irazola, L. Gutierrez, et al. 2018. “Association Between Household air Pollution Exposure and Chronic Obstructive Pulmonary Disease Outcomes in 13 low-and Middle-Income Country Settings.” American Journal of Respiratory and Critical Care Medicine 197 (5): 611–620.
   PubMed Web of Science ®Google Scholar
• Sirkeci, I., and M. M. Yucesahin. 2020. “Coronavirus and Migration: Analysis of Human Mobility and the Spread of COVID-19.” Migration Letters 17 (2): 379–398.
   Web of Science ®Google Scholar
• Tian, H., Y. Liu, Y. Li, C. H. Wu, B. Chen, M. U. Kraemer, and B. Wang. 2020. “An Investigation of Transmission Control Measures During the First 50 Days of the COVID-19 Epidemic in China.” Science 368 (6491): 638–642.
   PubMed Web of Science ®Google Scholar
• Warren, M. S., and S. W. Skillman. 2020. “Mobility Changes in Response to COVID-19.” arXiv preprint arXiv:2003.14228.
   Google Scholar
• WHO. 2020a. Coronavirus Disease (COVID-19) - Events as they Happen [Internet]. World Health Organization. Accessed June 23, 2020. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/events-as-they-happen.
   Google Scholar
• WHO. 2020b. Coronavirus Disease (COVID-2019) Situation Reports-192. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200730-covid-19-sitrep-192.pdf?sfvrsn=5e52901f_8.
   Google Scholar
• Xu, S., and Y. Li. 2020. “Beware of the Second Wave of COVID-19.” The Lancet 395 (10233): 1321–1322.
   PubMed Web of Science ®Google Scholar
• Yang, C., D. Sha, Q. Liu, Y. Li, H. Lan, W. W. Guan, Tao Hu, et al. 2020. “Taking the Pulse of COVID-19: A Spatiotemporal Perspective.” arXiv preprint: arXiv:2005.04224.
   Google Scholar
• Zhang, D., J. Huang, Y. Li, F. Zhang, C. Xu, and T. He. 2014, September. “Exploring Human Mobility with Multi-source Data at Extremely Large Metropolitan Scales.” Proceedings of the 20th annual international conference on Mobile Computing and Networking, 201–212.
   Google Scholar