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Articles

Human mobility data in the COVID-19 pandemic: characteristics, applications, and challenges

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Pages 1126-1147 | Received 21 Feb 2021, Accepted 02 Jul 2021, Published online: 14 Jul 2021

References

  • Aleta, A., D. Martin-Corral, A. P. Piontti, M. Ajelli, M. Litvinova, M. Chinazzi, N. E. Dean, et al. 2020. “Modelling the Impact of Testing, Contact Tracing and Household Quarantine on Second Waves of COVID-19.” Nature Human Behaviour 4 (9): 964–971.
  • Alfano, V., and S. Ercolano. 2020. “The Efficacy of Lockdown Against COVID-19: A Cross-Country Panel Analysis.” Applied Health Economics and Health Policy 18 (4): 509–517.
  • Apple Inc. 2020. Mobility Trends Reports. July 14. https://covid19.apple.com/mobility.
  • Baidu Inc. 2020. Baidu Migration Data. April 1. https://qianxi.baidu.com/.
  • Bao, R., and A. Zhang. 2020. “Does Lockdown Reduce Air Pollution? Evidence from 44 Cities in Northern China.” Science of the Total Environment 731 (2020): 1–12. doi:https://doi.org/10.1016/j.scitotenv.2020.139052.
  • Belik, V., T. Geisel, and D. Brockmann. 2011. “Natural Human Mobility Patterns and Spatial Spread of Infectious Diseases.” Physical Review X 1 (1): 011001.
  • Beria, P., and V. Lunkar. 2021. “Presence and Mobility of the Population During the First Wave of Covid-19 Outbreak and Lockdown in Italy.” Sustainable Cities and Society 65: 102616.
  • Bisanzio, D., M. U. Kraemer, I. I. Bogoch, T. Brewer, J. S. Brownstein, and R. Reithinger. 2020. “Use of Twitter Social Media Activity as a Proxy for Human Mobility to Predict the Spatiotemporal Spread of COVID-19 at Global Scale.” Geospatial Health 15 (1): 19–24. doi:https://doi.org/10.4081/gh.2020.882.
  • Bogoch, I. I., A. Watts, A. Thomas-Bachli, C. Huber, M. U. Kraemer, and K. Khan. 2020. “Potential for Global Spread of a Novel Coronavirus from China.” Journal of Travel Medicine 27 (2): taaa011.
  • Brodeur, A., N. Cook, and T. Wright. 2021. “On the Effects of COVID-19 Safer-at-Home Policies on Social Distancing, Car Crashes and Pollution.” Journal of Environmental Economics and Management 106: 102427.
  • Bryant, P., and A. Elofsson. 2020. “Estimating the Impact of Mobility Patterns on COVID-19 Infection Rates in 11 European Countries.” PeerJ 8: e9879.
  • Camber Systems. 2020. Social Distancing Reporter. https://covid19.cambersystems.com/.
  • Cartenì, A., L. Di Francesco, and M. Martino. 2020. “How Mobility Habits Influenced the Spread of the COVID-19 Pandemic: Results from the Italian Case Study.” Science of the Total Environment 741: 140489.
  • Cartenì, A., L. Di Francesco, and M. Martino. 2021, January. “The Role of Transport Accessibility within the Spread of the Coronavirus Pandemic in Italy.” Safety Science 133: 104999. doi:https://doi.org/10.1016/j.ssci.2020.104999.
  • Changruenngam, S., D. J. Bicout, and C. Modchang. 2020. “How the Individual Human Mobility Spatio-Temporally Shapes the Disease Transmission Dynamics.” Scientific Reports 10 (1): 1–13.
  • Chen, C., J. Ma, Y. Susilo, Y. Liu, and M. Wang. 2016. “The Promises of Big Data and Small Data for Travel Behavior (aka Human Mobility) Analysis.” Transportation Research Part C: Emerging Technologies 68: 285–299.
  • Chen, Z.-L., Q. Zhang, Y. Lu, Z.-M. Guo, X. Zhang, W.-J. Zhang, C. Guo, et al. 2020. “Distribution of the COVID-19 Epidemic and Correlation with Population Emigration from Wuhan, China.” Chinese Medical Journal 133 (9): 1044–1050. doi:https://doi.org/10.1097/CM9.0000000000000782.
  • Chen, X., A. Zhang, H. Wang, A. Gallaher, and X. Zhu. 2021. “Compliance and Containment in Social Distancing: Mathematical Modeling of COVID-19 Across Townships.” International Journal of Geographical Information Science 35 (3): 446–465.
  • Corrado, E. M. 2019. “Repositories, Trust, and the Coretrustseal.” Technical Services Quarterly 36 (1): 61–72.
  • Cuebiq Inc. 2020. Cuebiq's COVID-19 Mobility Index (CMI). October 1. https://help.cuebiq.com/hc/en-us/articles/360041285051-Cuebiq-s-COVID-19-Mobility-Index-CMI-.
  • 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): 1–14.
  • Delen, D., E. Eryarsoy, and B. Davazdahemami. 2020. “No Place Like Home: Cross-National Data Analysis of the Efficacy of Social Distancing During the COVID-19 Pandemic.” JMIR Public Health and Surveillance 6 (2): e19862.
  • De Montjoye, Y. A., C. A. Hidalgo, M. Verleysen, and V. D. Blondel. 2013. “Unique in the Crowd: The Privacy Bounds of Human Mobility.” Scientific Reports 3 (1): 1–5.
  • Descartes Lab. 2020. Descartes Lab Mobility Index. https://www.descarteslabs.com/mobility/.
  • Dickson, M. M., G. Espa, D. Giuliani, F. Santi, and L. Savadori. 2020. “Assessing the Effect of Containment Measures on the Spatio-Temporal Dynamic of COVID-19 in Italy.” Nonlinear Dynamics 101 (3): 1833–1846.
  • Djurović, I. 2020. “Epidemiological Control Measures and Predicted Number of Infections for SARS-CoV-2 Pandemic: Case Study Serbia March–April 2020.” Heliyon 6 (6): e04238.
  • Dudden, A., and A. Marks. 2020. “South Korea Took Rapid, Intrusive Measures against Covid-19-and They Worked.” The Guardian, 20.
  • Dwork, C., and A. Roth. 2014. “The Algorithmic Foundations of Differential Privacy.” Foundations and Trends® in Theoretical Computer Science 9 (3-4): 211–407.
  • Fan, C., Y. Li, J. Guang, Z. Li, A. Elnashar, M. Allam, and G. de Leeuw. 2020. “The Impact of the Control Measures during the COVID-19 Outbreak on Air Pollution in China.” Remote Sensing 12 (10): 1613.
  • Fang, H., L. Wang, and Y. Yang. 2020. “Human Mobility Restrictions and the Spread of the Novel Coronavirus (2019-ncov) in China.” Journal of Public Economics 191: 104272.
  • Fathi-Kazerooni, S., R. Rojas-Cessa, Z. Dong, and V. Umpaichitra. 2020. Time Series Analysis and Correlation of Subway Turnstile Usage and COVID-19 Prevalence in New York City. arXiv preprint arXiv:2008.08156.
  • Foursquare Labs, Inc. 2020. Location Visit Data. June 1. https://visitdata.org/index.html.
  • Fraiberger, S. P., P. Astudillo, L. Candeago, A. Chunet, N. K. Jones, M. F. Khan, B. Lepri, et al. 2020. Uncovering Socioeconomic Gaps in Mobility Reduction during the COVID-19 Pandemic Using Location Data. arXiv preprint arXiv:2006.15195.
  • Fraser, T., and D. P. Aldrich. 2021. “The Dual Effect of Social Ties on COVID-19 Spread in Japan.” Scientific Reports 11 (1): 1–12.
  • Gao, S., J. Rao, Y. Kang, Y. Liang, and J. Kruse. 2020a. “Mapping County-Level Mobility Pattern Changes in the United States in Response to COVID-19.” SIGSpatial Special 12 (1): 16–26.
  • Gao, J., J. Wang, Z. Bian, S. D. Bernardes, Y. Chen, A. Bhattacharyya, S. S. M. Thambiran, K. Ozbay, S. Iyer, and X. J. Ban. 2020b. The Effects of the COVID-19 Pandemic on Transportation Systems in New York City and Seattle, USA. arXiv preprint arXiv:2010.01170.
  • 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.
  • Ghader, S., J. Zhao, M. Lee, W. Zhou, G. Zhao, and L. Zhang. 2020. Observed Mobility Behavior Data Reveal Social Distancing Inertia. arXiv 2020; published online April 30, 2020. https://arxiv.org/abs/2004.14748 (preprint).
  • Gharehgozli, O., P. Nayebvali, A. Gharehgozli, and Z. Zamanian. 2020. “Impact of COVID-19 on the Economic Output of the US Outbreak’s Epicenter.” Economics of Disasters and Climate Change 4 (3): 561–573.
  • Gonzalez, M. C., C. A. Hidalgo, and A. L. Barabasi. 2008. “Understanding Individual Human Mobility Patterns.” Nature 453 (7196): 779–782.
  • Google LLC. 2020. Google COVID-19 Community Mobility Reports. May 14. https://www.google.com/covid19/mobility/.
  • Gudivada, V. N., R. Baeza-Yates, and V. V. Raghavan. 2015. “Big Data: Promises and Problems.” Computer 48: 20–23.
  • Hadjidemetriou, G. M., M. Sasidharan, G. Kouyialis, and A. K. Parlikad. 2020. “The Impact of Government Measures and Human Mobility Trend on COVID-19 Related Deaths in the UK.” Transportation Research Interdisciplinary Perspectives 6: 100167.
  • Haider, N., A. Yavlinsky, D. Simons, A. Y. Osman, F. Ntoumi, A. Zumla, and R. Kock. 2020. “Passengers’ Destinations from China: Low Risk of Novel Coronavirus (2019-nCoV) Transmission Into Africa and South America.” Epidemiology & Infection 148: 1–7.
  • Hu, T., W. W. Guan, X. Zhu, Y. Shao, L. Liu, J. Du, H. Liu, et al. 2020a. “Building an Open Resources Repository for COVID-19 Research.” Data and Information Management 4 (3): 130–147. https://doi.org/https://doi.org/10.2478/dim-2020-0012.
  • Hu, M., H. Lin, J. Wang, C. Xu, A. J. Tatem, B. Meng, X. Zhang, et al. 2020b. “The Risk of COVID-19 Transmission in Train Passengers: An Epidemiological and Modelling Study.” Clinical Infectious Diseases.
  • Hu, T., B. She, L. Duan, H. Yue, and J. Clunis. 2020c. “A Systematic Spatial and Temporal Sentiment Analysis on Geo-Tweets.” IEEE Access 8: 8658–8667.
  • 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.
  • Huang, X., Z. Li, Y. Jiang, X. Ye, C. Deng, J. Zhang, and X. Li. 2020b. “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.” International Journal of Digital Earth. doi:https://doi.org/10.1080/17538947.2021.1886358.
  • Huang, X., Z. Li, J. Lu, S. Wang, H. Wei, and B. Chen. 2020c. “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.
  • Huang, X., C. Wang, and Z. Li. 2018. “A Near Real-Time Flood-Mapping Approach by Integrating Social Media and Post-Event Satellite Imagery.” Annals of GIS 24 (2): 113–123.
  • Iacus, S. M., F. Natale, C. Santamaria, S. Spyratos, and M. Vespe. 2020. “Estimating and Projecting Air Passenger Traffic During the COVID-19 Coronavirus Outbreak and Its Socioeconomic Impact.” Safety Science 129: 1–11.
  • Jeffrey, B., C. E. Walters, K. E. Ainslie, O. Eales, C. Ciavarella, S. Bhatia, S. Hayes, et al. 2020. “Anonymised and Aggregated Crowd Level Mobility Data from Mobile Phones Suggests That Initial Compliance with COVID-19 Social Distancing Interventions was High and Geographically Consistent Across the UK.” Wellcome Open Research : 5–170. https://doi.org/https://doi.org/10.12688/wellcomeopenres.15997.1.
  • Jiang, J., and L. Luo. 2020. “Influence of Population Mobility on the Novel Coronavirus Disease (COVID-19) Epidemic: Based on Panel Data from Hubei, China.” Global Health Research and Policy 5 (1): 1–10.
  • Jurdak, R., K. Zhao, J. Liu, M. AbouJaoude, M. Cameron, and D. Newth. 2015. “Understanding Human Mobility from Twitter.” PLoS ONE 10 (7): 1–16. doi:https://doi.org/10.1371/journal.pone.0131469.
  • Kang, Y., S. Gao, Y. Liang, M. Li, J. Rao, and J. Kruse. 2020. “Multiscale Dynamic Human Mobility Flow Dataset in the U.S. during the COVID-19 Epidemic.” Scientific Data 7 (1): 1–13.
  • Kaur, S., H. Bherwani, S. Gulia, R. Vijay, and R. Kumar. 2021. “Understanding COVID-19 Transmission, Health Impacts and Mitigation: Timely Social Distancing is the key.” Environment, Development and Sustainability 23: 6681–6697. doi:https://doi.org/10.1007/s10668-020-00884-x.
  • Kondor, D., B. Hashemian, Y. A. de Montjoye, and C. Ratti. 2020. “Towards Matching User Mobility Traces in Large-Scale Datasets.” IEEE Transactions on Big Data 6 (4): 714–726.
  • Kraemer, M. U., C. H. Yang, B. Gutierrez, C. H. Wu, B. Klein, D. M. Pigott, L. du Plessis, et al. 2020. “The Effect of Human Mobility and Control Measures on the COVID-19 Epidemic in China.” Science 368 (6490): 493–497.
  • Kuchler, T., D. Russel, and J. Stroebel. 2020. The Geographic Spread of COVID-19 Correlates with the Structure of Social Networks as Measured by Facebook (No. w26990). National Bureau of Economic Research. https://www.nber.org/papers/w26990.
  • Kurita, J., Y. Sugishita, T. Sugawara, and Y. Ohkusa. 2021. “Evaluating Apple Inc Mobility Trend Data Related to the COVID-19 Outbreak in Japan: Statistical Analysis.” JMIR Public Health and Surveillance 7 (2): e20335.
  • Lamb, M. R., S. Kandula, and J. Shaman. 2020. “Differential COVID-19 Case Positivity in New York City Neighborhoods: Socioeconomic Factors and Mobility.” Influenza and Other Respiratory Viruses. doi:https://doi.org/10.1111/irv.12816.
  • Lau, H., V. Khosrawipour, P. Kocbach, A. Mikolajczyk, J. Schubert, J. Bania, and T. Khosrawipour. 2020. “The Positive Impact of Lockdown in Wuhan on Containing the COVID-19 Outbreak in China.” Journal of Travel Medicine 27 (3): taaa037.
  • 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.
  • Lee, M., J. Zhao, Q. Sun, Y. Pan, W. Zhou, C. Xiong, and L. Zhang. 2020. Human Mobility Trends during the COVID-19 Pandemic in the United States. arXiv 2020; published online May 4. http://arxiv.org/abs/2005.01215 (preprint).
  • Levin, R., D. L. Chao, E. A. Wenger, and J. L. Proctor. 2020. “Cell Phone Mobility Data Reveals Heterogeneity in Stay-at-Home Behavior during the SARS-CoV-2 Pandemic.” medRxiv. doi:https://doi.org/10.1101/2020.10.31.20223776.
  • Li, Z. 2020. “Geospatial big Data Handling with High Performance Computing: Current Approaches and Future Directions.” In High Performance Computing for Geospatial Applications, edited by W. Tang and S. Wang, 53–76. Cham: Springer.
  • Li, Z., X. Huang, T. Hu, H. Ning, X. Ye, and X. Li. 2021a. ODT FLOW: A Scalable Platform for Extracting, Analyzing, and Sharing Multi-Source Multi-Scale Human Mobility. arXiv preprint arXiv:2104.05040.
  • Li, Z., X. Huang, X. Ye, Y. Jiang, M. Yago, H. Ning, M. E. Hodgson, and X. Li. 2021b. Measuring Place Connectivity Using Big Social Media Data. arXiv preprint arXiv:2102.03991.
  • Li, Z., X. Huang, X. Ye, and X. Li. 2020a. ODT Flow Explorer: Extract, Query, and Visualize Human Mobility. arXiv preprint arXiv:2011.12958.
  • Li, Z., X. Li, D. Porter, J. Zhang, Y. Jiang, B. Olatosi, and S. Weissman. 2020b. “Monitoring the Spatial Spread of COVID-19 and Effectiveness of Control Measures Through Human Movement Data: Proposal for a Predictive Model Using Big Data Analytics.” JMIR Research Protocols 9 (12): e24432.
  • Liu, M., J. Ning, Y. Du, J. Cao, D. Zhang, J. Wang, and M. Chen. 2020a. “Modelling the Evolution Trajectory of COVID-19 in Wuhan, China: Experience and Suggestions.” Public Health 183: 76–80.
  • Liu, Q., D. Sha, W. Liu, P. Houser, L. Zhang, R. Hou, H. Lan, et al. 2020b. “Spatiotemporal Patterns of COVID-19 Impact on Human Activities and Environment in Mainland China Using Night-Time Light and air Quality Data.” Remote Sensing 12 (10): 1576.
  • Liu, Y., S. Wang, and B. Xie. 2019. “Evaluating the Effects of Public Transport Fare Policy Change Together with Built and Non-Built Environment Features on Ridership: The Case in South East Queensland, Australia.” Transport Policy 76: 78–89.
  • Martín, Y., S. L. Cutter, Z. Li, C. Emrich, and J. T. Mitchell. 2020. “Using Geotagged Tweets to Track Population Movements to and from Puerto Rico After Hurricane Maria.” Population and Environment. doi:https://doi.org/10.1007/s11111-020-00338-6.
  • Meloni, S., N. Perra, A. Arenas, S. Gómez, Y. Moreno, and A. Vespignani. 2011. “Modeling Human Mobility Responses to the Large-Scale Spreading of Infectious Diseases.” Scientific Reports 1 (1): 1–7.
  • Mohammadi, H., A. Rajabifard, and I. P. Williamson. 2010. “Development of an Interoperable Tool to Facilitate Spatial Data Integration in the Context of SDI.” International Journal of Geographical Information Science 24 (4): 487–505.
  • 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.
  • Ni, S., and W. Weng. 2009. “Impact of Travel Patterns on Epidemic Dynamics in Heterogeneous Spatial Metapopulation Networks.” Physical Review E 79 (1): 016111.
  • Oliver, N., B. Lepri, H. Sterly, R. Lambiotte, S. Deletaille, M. De Nadai, E. Letouzé, et al. 2020. “Mobile Phone Data for Informing Public Health Actions across the COVID-19 Pandemic Life Cycle.” Science Advances 6: eabc0764.
  • The OpenSky Network. 2020. http://www.opensky-network.org.
  • O’Sullivan, D., M. Gahegan, D. J. Exeter, and B. Adams. 2020. “Spatially Explicit Models for Exploring COVID-19 Lockdown Strategies.” Transactions in GIS 24 (4): 967–1000.
  • Pan, Y., A. Darzi, A. Kabiri, G. Zhao, W. Luo, C. Xiong, and L. Zhang. 2020. “Quantifying Human Mobility Behavior Changes in Response to Non-Pharmaceutical Interventions during the COVID-19 Outbreak in the United States.” arXiv 2020; published online May 4, 2020. http://arxiv.org/abs/2005.01224 (preprint).
  • Park, Y. J., Y. J. Choe, O. Park, S. Y. Park, Y. M. Kim, J. Kim, S. Kweon, et al. 2020. “Contact Tracing During Coronavirus Disease Outbreak, South Korea, 2020.” Emerging Infectious Diseases 26 (10): 2465–2468.
  • Peng, Z., R. Wang, L. Liu, and H. Wu. 2020. “Exploring Urban Spatial Features of COVID-19 Transmission in Wuhan Based on Social Media Data.” ISPRS International Journal of Geo-Information 9 (6): 402.
  • Pepe, E., P. Bajardi, L. Gauvin, F. Privitera, B. Lake, C. Cattuto, and M. Tizzoni. 2020. “COVID-19 Outbreak Response, a Dataset to Assess Mobility Changes in Italy Following National Lockdown.” Scientific Data 7 (1): 1–7.
  • Porcher, Simon, and Thomas Renault. 2020. “Social Distancing Beliefs and Human Mobility: Evidence from Twitter.” arXiv preprint arXiv:2008.04826. https://arxiv.org/abs/2008.04826.
  • Rutz, C., M. C. Loretto, A. E. Bates, S. C. Davidson, C. M. Duarte, W. Jetz, M. Johnson, et al. 2020. “COVID-19 Lockdown Allows Researchers to Quantify the Effects of Human Activity on Wildlife.” Nature Ecology & Evolution 4 (9): 1156–1159.
  • SafeGraph Inc. 2020. SafeGraph COVID-19 Data. October 1. https://www.safegraph.com/covid-19-data-consortium.
  • Salathé, M., C. L. Althaus, R. Neher, S. Stringhini, E. Hodcroft, J. Fellay, M. Zwahlen, et al. 2020. “COVID-19 Epidemic in Switzerland: On the Importance of Testing, Contact Tracing and Isolation.” Swiss Medical Weekly 150 (11-12): w20225.
  • Shen, J. 2020. “Covid-19 and Inter-Provincial Migration in China.” Eurasian Geography and Economics 61 (4-5): 620–626.
  • Song, C., Z. Qu, N. Blumm, and A. L. Barabási. 2010. “Limits of Predictability in Human Mobility.” Science 327 (5968): 1018–1021.
  • Su, Y., J. Xue, X. Liu, P. Wu, J. Chen, C. Chen, T. Liu, W. Gong, and T. Zhu1. 2020. “Examining the Impact of COVID-19 Lockdown in Wuhan and Lombardy: A Psycholinguistic Analysis on Weibo and Twitter.” International Journal of Environmental Research and Public Health 17 (12): 4552. doi:https://doi.org/10.3390/ijerph17124552.
  • Tobías, A. 2020. “Evaluation of the Lockdowns for the SARS-CoV-2 Epidemic in Italy and Spain After one Month Follow Up.” Science of The Total Environment 725: 138539.
  • Torre-Bastida, A. I., J. Del Ser, I. Laña, M. Ilardia, M. N. Bilbao, and S. Campos-Cordobés. 2018. “Big Data for Transportation and Mobility: Recent Advances, Trends and Challenges.” IET Intelligent Transport Systems 12 (8): 742–755.
  • Unacast. 2020. Social Distancing Scoreboard. COVID-19 Toolkit. https://www.unacast.com/covid19/social-distancing-scoreboard.
  • University of Maryland. 2020. University of Maryland COVID-19 Impact Analysis Platform,https://data.covid.umd.edu.
  • Usery, E. L., M. P. Finn, M. Starbuck, and M. C. M. Center. 2005. “Integrating Data Layers to Support the National Map of the United States.” In International Cartographic Conference. A Corua, Spain.
  • Vokó, Z., and J. G. Pitter. 2020. “The Effect of Social Distance Measures on COVID-19 Epidemics in Europe: An Interrupted Time Series Analysis.” GeroScience 42 (4): 1075–1082.
  • Wang, S., Y. Liu, and T. Hu. 2020. “Examining the Change of Human Mobility Adherent to Social Restriction Policies and its Effect on COVID-19 Cases in Australia.” International Journal of Environmental Research and Public Health 17 (21): 7930.
  • Warren, M. S., and S. W. Skillman. 2020. “Mobility Changes in Response to COVID-19.” arXiv preprint arXiv:2003.14228.
  • Watts, A., N. H. Au, A. Thomas-Bachli, J. Forsyth, O. Mayah, S. Popescu, and I. I. Bogoch. 2020. “Potential for Inter-State Spread of Covid-19 from Arizona, USA: Analysis of Mobile Device Location and Commercial Flight Data.” Journal of Travel Medicine 27 (8): 1–3. doi:https://doi.org/10.1093/jtm/taaa136.
  • Xiong, C., S. Hu, M. Yang, H. N. Younes, W. Luo, S. Ghader, and L. Zhang. 2020. “Data-Driven Modeling Reveals the Impact of Stay-at-Home Orders on Human Mobility during the COVID-19 Pandemic in the U.S.” arXiv 2020; published online May 2. http://arxiv.org/abs/2005.00667 (preprint).
  • Xu, Y., A. Belyi, I. Bojic, and C. Ratti. 2018. “Human Mobility and Socioeconomic Status: Analysis of Singapore and Boston.” Computers, Environment and Urban Systems 72: 51–67.
  • Xu, F., Z. Tu, Y. Li, P. Zhang, X. Fu, and D. Jin. 2017. “Trajectory Recovery from Ash: User Privacy Is Not Preserved in Aggregated Mobility Data.” Proceedings of the 26th International Conference on World Wide Web.
  • Xu, X., S. Wang, J. Dong, Z. Shen, and S. Xu. 2020. “An Analysis of the Domestic Resumption of Social Production and Life under the COVID-19 Epidemic.” PLoS ONE 15 (7): e0236387.
  • Yabe, T., K. Tsubouchi, N. Fujiwara, T. Wada, Y. Sekimoto, and S. V. Ukkusuri. 2020. “Non-Compulsory Measures Sufficiently Reduced Human Mobility in Tokyo during the COVID-19 Epidemic.” Scientific Reports 10 (1): 1–9.
  • Yang, C., D. Sha, Q. Liu, Y. Li, H. Lan, W. W. Guan, T. Hu, et al. 2020. “Taking the Pulse of COVID-19: A Spatiotemporal Perspective.” International Journal of Digital Earth 13 (10): 1186–1211.
  • Yue, H., and T. Hu. 2021. “Geographical Detector-Based Spatial Modeling of the COVID-19 Mortality Rate in the Continental United States.” International Journal of Environmental Research and Public Health 18 (13): 6832.
  • Zang, H., and J. Bolot. 2011. “Anonymization of Location Data Does Not Work: A Large-Scale Measurement Study.” Proceedings of the 17th Annual International Conference on Mobile Computing and Networking.
  • Zeng, C., J. Zhang, Z. Li, X. Sun, B. Olatosi, S. Weissman, and X. Li. 2021. “Spatial-Temporal Relationship between Population Mobility and COVID-19 Outbreaks in South Carolina: A Time Series Forecasting Analysis.” medRxiv. doi:https://doi.org/10.1101/2021.01.02.21249119.
  • Zhang, D., J. Huang, Y. Li, F. Zhang, C. Xu, and T. He. 2014. “Exploring Human Mobility with multi-Source Data at Extremely Large Metropolitan Scales.” In Proceedings of the 20th Annual International Conference on Mobile Computing and Networking. 201–212. September.
  • Zhao, K., S. Tarkoma, S. Liu, and H. Vo. 2016. “Urban Human Mobility Data Mining: An Overview.” In 2016 IEEE International Conference on Big Data (Big Data). 1911–1920. December. IEEE.
  • Zhou, Y., L. Wang, L. Zhang, L. Shi, K. Yang, J. He, B. Zhao, W. Overton, S. Purkayastha, and P. Song. 2020. “A Spatiotemporal Epidemiological Prediction Model to Inform County-Level COVID-19 Risk in the United States.” Special Issue 1-COVID-19: Unprecedented Challenges and Chances.
  • Zhuang, Z., P. Cao, S. Zhao, Y. Lou, W. Wang, S. Yang, W. Wang, L. Yang, and D. He. 2020. “Estimation of Local Novel Coronavirus (COVID-19) Cases in Wuhan, China from Off-Site Reported Cases and Population Flow Data from Different Sources.” medRxiv.
  • Zikopoulos, P., and C. Eaton. 2011. Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. New York: McGraw-Hill.

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