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Research Article

Population mobility change for controlling the transmission of COVID-19: mobile phone data analysis in nine cities of China

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Pages 627-641 | Received 24 Jan 2022, Accepted 04 Aug 2023, Published online: 31 Oct 2023

References

  • Arif, M., M. Hasan, S. M. Alawi, and M. A. Naeem. 2021. “COVID-19 and Time-Frequency Connectedness Between Green and Conventional Financial Markets.” Global Finance Journal 49: 100650. https://doi.org/10.1016/j.gfj.2021.100650.
  • Chakrabarti, S., L. C. Hamlet, J. Kaminsky, and S. V. Subramanian. 2021. “Association of Human Mobility Restrictions and Race/ethnicity–Based, Sex-Based, and Income-Based Factors with Inequities in Well-Being During the COVID-19 Pandemic in the United States.” JAMA Network Open 4 (4): e217373. https://doi.org/10.1001/jamanetworkopen.2021.7373.
  • Chinazzi, M., J. T. Davis, M. Ajelli, C. Gioannini, M. Litvinova, S. Merler, A. Pastore y Piontti, et al. 2020. “The Effect of Travel Restrictions on the Spread of the 2019 Novel Coronavirus (COVID-19) Outbreak.” Science 368 (6489): 395–400. https://doi.org/10.1126/science.aba9757.
  • Deloitte. 2018. “Chinese Consumers at the Forefront of Digital Technologies: China Mobile Consumer Survey 2018.” Accessed April 26, 2020. https://www2.deloitte.com/content/dam/Deloitte/cn/Documents/technology-mediatelecommunications/deloitte-cn-2018-mobile-consumer-survey-en-190121.pdf.
  • Ferretti, L., C. Wymant, M. Kendall, L. Zhao, A. Nurtay, D. G. Bonsall, C. F. C. Fraser, et al. 2020. “Quantifying Dynamics of SARS-CoV-2 Transmission Suggests That Epidemic Control and Avoidance is Feasible Through Instantaneous Digital Contact Tracing.” medRxiv. https://doi.org/10.1101/2020.03.08.20032946.
  • Finger, F., T. Genolet, L. Mari, G. C. de Magny, N. M. Manga, A. Rinaldo, and E. Bertuzzo. 2016. “Mobile Phone Data Highlights the Role of Mass Gatherings in the Spreading of Cholera Outbreaks.” PNAS 113 (23): 6421–6426. https://doi.org/10.1073/pnas.1522305113.
  • Fong, M. W., H. Gao, J. Y. Wong, J. Xiao, E. Y. Shiu, S. Ryu, and B. J. Cowling. 2020. “Nonpharmaceutical Measures for Pandemic Influenza in Nonhealthcare Settings—Social Distancing Measures.” Emerging Infectious Diseases 26 (5): 976–984. https://doi.org/10.3201/eid2605.190995.
  • Fu, Z., Z. Tian, Y. Xu, and C. Qiao. 2016. “A Two-Step Clustering Approach to Extract Locations from Individual GPS Trajectory Data.” ISPRS International Journal of Geo-Information 5 (10): 166. Pérez. https://doi.org/10.3390/ijgi5100166.
  • Gonzalez, M. C., C. A. Hidalgo, and Barabasi A-L. 2008. “Understanding Individual Human Mobility Patterns.” Nature 453 (7196): 779–782. https://doi.org/10.1038/nature06958.
  • Hartley, D. M., Perencevich, E. N. 2020. “Public Health Interventions for COVID-19: Emerging Evidence and Implications for an Evolving Public Health Crisis.” JAMA 323 (19): 1908. https://doi.org/10.1001/jama.2020.5910.
  • Huang, Q., and D. W. S. Wong. 2016. “Activity Patterns, Socioeconomic Status and Urban Spatial Structure: What Can Social Media Data Tell Us?” International Journal of Geographical Information Science 30 (9): 1873–1898. https://doi.org/10.1080/13658816.2016.1145225.
  • Jia, J. S., X. Lu, Y. Yuan, G. Xu, J. Jia, and Christakis N. A. 2020. “Population Flow Drives Spatio-Temporal Distribution of COVID-19 in China.” Nature 582 (7812): 389–394. https://doi.org/10.1038/s41586-020-2284-y.
  • Klein, B., T. LaRocky, S. McCabey, L. Torresy, F. Privitera, B. Lake, et al. “Assessing Changes in Commuting and Individual Mobility in Major Metropolitan Areas in the United States During the COVID-19 Outbreak.” Accessed April 26, 2020. https://uploads-ssl.webflow.com/5c9104426f6f88ac129ef3d2/5e8374ee75221201609ab586_Assessing_mobility_changes_in_the_United_States_during_the_COVID_19_outbreak.pdf.
  • Kraemer, M. U., C.-H. Yang, B. Gutierrez, C.-H. Wu, B. Klein, D. M. Pigott, L. Du Plessis, N. R. Faria, R. Li, and W. P. Hanage. 2020. “The Effect of Human Mobility and Control Measures on the COVID-19 Epidemic in China.” Science 368 (6490): 493–497. https://doi.org/10.1126/science.abb4218.
  • Lai, S., N. W. Ruktanonchai, L. Zhou, O. Prosper, W. Luo, J. R. Floyd, and A. Wesolowski. 2020. “Effect of Non-Pharmaceutical Interventions for Containing the COVID-19 Outbreak: An Observational and Modelling Study.” medRxiv. https://doi.org/10.1101/2020.03.03.20029843.
  • Lemaitre J. C., J. Perez-Saez, Azman A. S., A. Rinaldo, and J. Fellay. 2020. “Assessing the Impact of Non-Pharmaceutical Interventions on SARS-CoV-2 Transmission in Switzerland.” Swiss Medical Weekly 150 (2122): 100650. 49. https://doi.org/10.4414/smw.2020.20295.
  • Li, M., S. Gao, F. Lu, H. J. C. Zhang, and Environment, Systems U. 2019. “Reconstruction of Human Movement Trajectories from Large-Scale Low-Frequency Mobile Phone Data.” Computers, Environment and Urban Systems 77: 101346. https://doi.org/10.1016/j.compenvurbsys.2019.101346.
  • Li, Q., X. Guan, P. Wu, X. Wang, L. Zhou, Y. Tong, R. Ren, et al. 2020. “Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia.” The New England Journal of Medicine 382 (13): 1199–1207. 10.1056/NEJMoa2001316.
  • Li, R., S. Pei, B. Chen, Y. Song, T. Zhang, W. Yang, J. Shaman, et al. 2020. “Substantial Undocumented Infection Facilitates the Rapid Dissemination of Novel Coronavirus (SARS-CoV-2).” Science 368 (6490): 489–493. https://doi.org/10.1126/science.abb3221.
  • Mansour, S., A. Abulibdeh, M. Alahmadi, and E. Ramadan. 2021. “Spatial Assessment of COVID-19 First-Wave Mortality Risk in the Global South.” The Professional Geographer 74 (3): 1–19. https://doi.org/10.1080/00330124.2021.2009888.
  • Masso, A., S. Silm, and R. Ahas. 2019. “Generational Differences in Spatial Mobility: A Study with Mobile Phone Data.” Population, Space and Place 25 (2): e2210. https://doi.org/10.1002/psp.2210.
  • Niu, B., R. Liang, S. Zhang, H. Zhang, X. Qu, Q. Su, L. Zheng, and Q. Chen. 2021. “Epidemic Analysis of COVID‐19 in Italy Based on Spatiotemporal Geographic Information and Google Trends.” Transboundary and Emerging Diseases 68 (4): 2384–2400. https://doi.org/10.1111/tbed.13902.
  • Noland, R. B. 2021. “Mobility and the Effective Reproduction Rate of COVID-19.” Journal of Transport & Health 20: 101016. https://doi.org/10.1016/j.jth.2021.101016.
  • Nouvellet, P., S. Bhatia, A. Cori, K. E. C. Ainslie, M. Baguelin, S. Bhatt, A. Boonyasiri, et al. 2021. “Reduction in Mobility and COVID-19 Transmission.” Nature Communications 12 (1): 1–9. https://doi.org/10.1038/s41467-021-21358-2.
  • Paez, A., F. A. Lopez, T. Menezes, R. Cavalcanti, and M. G. D. R. Pitta. 2021. “A Spatio‐Temporal Analysis of the Environmental Correlates of COVID‐19 Incidence in Spain.” Geographical Analysis 53 (3): 397–421. https://doi.org/10.1111/gean.12241.
  • Pei, S., S. Kandula, and J. Shaman. 2020. “Differential Effects of Intervention Timing on COVID-19 Spread in the United States.” Science Advances 6 (49): eabd6370. https://doi.org/10.1126/sciadv.abd6370.
  • Pepe, E., P. Bajardi, L. Gauvin, F. Privitera, B. Lake, C. Cattuto, and M. Tizzoni. 2020. “COVID-19 Outbreak Response: A First Assessment of Mobility Changes in Italy Following National Lockdown.” medRxiv. https://doi.org/10.1101/2020.03.22.20039933.
  • Pew Research Center. 2017. “China Outpaces India in Internet Access, Smartphone Ownership.” Accessed April 5, 2020. https://www.pewresearch.org/fact-tank/2017/03/16/china-outpaces-india-in-internet-access-smartphone-ownership.
  • Pullano, G., F. Pinotti, E. Valdano, P.-Y. Boëlle, C. Poletto, and V. J. E. Colizza. 2020. “Novel Coronavirus (2019-nCov) Early-Stage Importation Risk to Europe, January 2020.” Eurosurveillance 25 (4): 2000057. https://doi.org/10.2807/1560-7917.ES.2020.25.4.2000057.
  • Queiroz, L., A. Ferraz, J. L. Melo, G. Barboza, A. H. Urbanski, A. Nicolau, S. Oliva, and H. Nakaya. 2020. “Large-Scale Assessment of Human Mobility During COVID-19 Outbreak.” OSF Preprints. https://doi.org/10.31219/osf.io/nqxrd.
  • Shaw, S.-L., and M.-H. Tsou. 2016. “Human Dynamics in the Mobile and Big Data Era.” International Journal of Geographical Information Science 30 (9): 1687–1693. Ye XJIJoGIS. https://doi.org/10.1080/13658816.2016.1164317.
  • Shenzhen Government. 2020. “Data About COVID-19.” Accessed April 16, 2020. https://opendata.sz.gov.cn/data/dataSet/toDataDetails/29200_01503668.
  • Shenzhen Statistics Department. “2018. Bulletin of Main Statistics from the National Census in Shenzhen.” Accessed March 3, 2020. http://tjj.sz.gov.cn/ztzl/zt/sjfb/.
  • Silm, S., R. Ahas, and M. Nuga. 2013. “Gender Differences in Space—Time Mobility Patterns in a Postcommunist City: A Case Study Based on Mobile Positioning in the Suburbs of Tallinn.” Environment & Planning B: Planning & Design 40 (5): 814–828. e2210. https://doi.org/10.1068/b38068.
  • Song Gao, J. R., Y. Kang, Y. Liang, J. Kruse, D. Doepfer, A. K. Sethi, J. Francisco Mandujano Reyes, J. Patz, and B. S. Yandell. 2020. “Mobile Phone Location Data Reveal the Effect and Geographic Variation of Social Distancing on the Spread of the COVID-19.” epidemic. arXiv preprint arXiv. https://arxiv.org/pdf/2004.11430.pdf.
  • Song, C., Z. Qu, N. Blumm, and A.-L. Barabási. 2010. “Limits of Predictability in Human Mobility.” Science 327 (5968): 1018–1021. https://doi.org/10.1126/science.1177170.
  • Tian, H., Y. Liu, Y. Li, C.-H. Wu, B. Chen, M. U. Kraemer, B. Li. 2020. “An Investigation of Transmission Control Measures During the First 50 Days of the COVID-19 Epidemic in China.” Science 368 (6491): 638–642. https://doi.org/10.1126/science.abb6105.
  • Torres, R., C. Torres-Huitzil, and H. Galeana-Zapién. 2016. “Full On-Device Stay Points Detection in Smartphones for Location-Based Mobile Applications.” Sensors 16 (10): 1693. https://doi.org/10.3390/s16101693.
  • Warren, M. S., and S. W. Skillman. 2020. “Mobility Changes in Response to COVID-19.” arXiv preprint arXiv. https://arxiv.org/abs/2003.14228.
  • Wesolowski, A., C. J. E. Metcalf, N. Eagle, J. Kombich, B. T. Grenfell, O. N. Bjørnstad, J. Lessler, A. J. Tatem, and C. O. Buckee. 2015. “Quantifying Seasonal Population Fluxes Driving Rubella Transmission Dynamics Using Mobile Phone Data.” Proceedings of the National Academy of Sciences 112 (35): 11114–11119. https://doi.org/10.1073/pnas.1423542112.
  • Wu, L., Y. Zhi, Z. Sui, Y. Liu, and V. Colizza. 2014. “Intra-Urban Human Mobility and Activity Transition: Evidence from Social Media Check-In Data.” PloS one 9 (5): e97010. https://doi.org/10.1371/journal.pone.0097010.
  • Xi, W., T. Pei, Q. Liu, C. Song, Y. Liu, X. Chen, J. Ma, and Z. Zhang. 2020. “Quantifying the Time-Lag Effects of Human Mobility on the COVID-19 Transmission: A Multi-City Study in China.” IEEE Access 8:216752–216761. https://doi.org/10.1101/2020.07.13.20148668.
  • Yue, Y., Y. Zhuang, A. G. Yeh, J.-Y. Xie, C.-L. Ma, and Li Q-QJIJoGIS. 2017. “Measurements of POI-Based Mixed Use and Their Relationships with Neighbourhood Vibrancy.” International Journal of Geographical Information Science 31 (4): 658–675. https://doi.org/10.1080/13658816.2016.1220561.
  • Zhang, Q., S. Feng, I. O. Wong, D. K. Ip, B. J. Cowling, and L. EHJBph. 2020. “A Population-Based Study on Healthcare-Seeking Behaviour of Persons with Symptoms of Respiratory and Gastrointestinal-Related Infections in Hong Kong.” BMC Public Health 20 (1): 1–10. https://doi.org/10.1186/s12889-020-08555-2.
  • Zhou, Y., R. Xu, D. Hu, Y. Yue, Q. Li, and J. Xia. 2020. “Effects of Human Mobility Restrictions on the Spread of COVID-19 in Shenzhen, China: A Modelling Study Using Mobile Phone Data.” Lancet Digital Health 2 (8): e417–e424. https://doi.org/10.1016/S2589-7500(20)30165-5.
  • Zuur, A. F., E. N. Ieno, N. J. Walker, A. A. Saveliev, and G. M. Smith. 2009. Mixed Effects Models and Extensions in Ecology with R, Vol. 574. New York: Springer New York. https://doi.org/10.1007/978-0-387-87458-6.