Chapter
May 24, 2022

Quantifying Mobility Perturbation in America’s Cities during COVID-19: A Network-Based Approach

Publication: Computing in Civil Engineering 2021

ABSTRACT

The pandemic of COVID-19 has caused severe disruptions in urban lives. Understanding and quantifying these disruptions is important to inform the development of targeted and effective measures to control the pandemic and its impact. One way of achieving this object is to measure the urban mobility perturbation caused by the pandemic. In this study, we built mobility-based networks for seven major metropolitan statistical areas (MSAs) across the United States in the years of 2019 and 2020, respectively. We quantified the disruptions of urban mobility by computing and comparing a set of network-based metrics before and during the pandemic. The proposed approach is able to uncover the impact of COVID-19 in cities and provides new insights into the resilience of cities when facing large-scale disasters.

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REFERENCES

Abu-Rayash, A., and Dincer, I. (2020). “Analysis of mobility trends during the COVID-19 coronavirus pandemic: Exploring the impacts on global aviation and travel in selected cities.” Energy research & social science, 68, 101693.
Armstrong, D. A., Lebo, M. J., and Lucas, J. (2020). “Do COVID-19 Policies Affect Mobility Behaviour? Evidence from 75 Canadian and American Cities.” Canadian Public Policy, 46(S2), S127–S144.
Brown, T. S., Engø-Monsen, K., Kiang, M. V., Mahmud, A. S., Maude, R. J., and Buckee, C. O. (2021). “The impact of mobility network properties on predicted epidemic dynamics in Dhaka and Bangkok.” Epidemics, 35, 100441.
Chakraborty, I., and Maity, P. (2020). “COVID-19 outbreak: Migration, effects on society, global environment and prevention.” Science of The Total Environment, 728, 138882.
D’Agata, R., Gozzo, S., and Tomaselli, V. (2013). “Network analysis approach to map tourism mobility.” Quality & Quantity, 47(6), 3167–3184.
Fiore, M., and Härri, J. (2008). “The networking shape of vehicular mobility.” Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing, Association for Computing Machinery, Hong Kong, Hong Kong, China, 261–272.
Freitas, V. L. S., Konstantyner, T., Mendes, J. F., Sepetauskas, C., and Santos, L. (2020). “The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in Brazil.” Cadernos de saúde pública/Ministério da Saúde, Fundação Oswaldo Cruz, Escola Nacional de Saúde Pública, 36(9), e00184820.
Glaeser, E. L., Gorback, C. S., and Redding, S. J. (2020). How much does COVID-19 increase with mobility? Evidence from New York and four other US cities. National Bureau of Economic Research.
Huang, X., Li, Z., Jiang, Y., Li, X., and Porter, D. (2020). “Twitter reveals human mobility dynamics during the COVID-19 pandemic.” PloS one, 15(11), e0241957.
Jia, J. S., Lu, X., Yuan, Y., Xu, G., Jia, J., and Christakis, N. A. (2020). “Population flow drives spatio-temporal distribution of COVID-19 in China.” Nature, 582(7812), 389–394.
Kang, Y., Gao, S., Liang, Y., Li, M., Rao, J., and Kruse, J. (2020). “Multiscale dynamic human mobility flow dataset in the US during the COVID-19 epidemic.” Scientific data, 7(1), 1–13.
Mo, B., Feng, K., Shen, Y., Tam, C., Li, D., Yin, Y., and Zhao, J. (2021). “Modeling epidemic spreading through public transit using time-varying encounter network.” Transportation Research Part C: Emerging Technologies, 122, 102893.
Ruiz-Euler, A., Privitera, F., Giuffrida, D., Lake, B., and Zara, I. (2020). “Mobility patterns and income distribution in times of crisis: US urban centers during the COVID-19 pandemic.” Available at SSRN 3572324.
SafeGraph. (2020). “Social Distancing Metrics.” <https://docs.safegraph.com/docs/social-distancing-metrics>(April 13, 2021).
Schlosser, F., Maier, B. F., Jack, O., Hinrichs, D., Zachariae, A., and Brockmann, D. (2020). “COVID-19 lockdown induces disease-mitigating structural changes in mobility networks.” Proceedings of the National Academy of Sciences, 117(52), 32883–32890.
So, M. K. P., Chu, A. M. Y., Tiwari, A., and Chan, J. N. L. (2021). “On topological properties of COVID-19: predicting and assessing pandemic risk with network statistics.” Scientific Reports, 11(1), 5112.
Wang, Q., and Taylor, J. E. (2014). “Quantifying human mobility perturbation and resilience in Hurricane Sandy.” PLoS One, 9 (11), e112608.
Yabe, T., Tsubouchi, K., Fujiwara, N., Wada, T., Sekimoto, Y., and Ukkusuri, S. V. (2020). “Non-compulsory measures sufficiently reduced human mobility in Tokyo during the COVID-19 epidemic.” Scientific Reports, 10(1), 18053.
Zhong, C., Arisona, S. M., Huang, X., Batty, M., and Schmitt, G. (2014). “Detecting the dynamics of urban structure through spatial network analysis.” International Journal of Geographical Information Science, 28(11), 2178–2199.

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Go to Computing in Civil Engineering 2021
Computing in Civil Engineering 2021
Pages: 1000 - 1007

History

Published online: May 24, 2022

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Ruoxi Wang, S.M.ASCE [email protected]
1Dept. of Construction Management, Tsinghua Univ., Beijing, China. Email: [email protected]
2Dept. of Civil and Environmental Engineering, Northeastern Univ., Boston, MA. Email: [email protected]
Nan Li, M.ASCE [email protected]
3Dept. of Construction Management, Tsinghua Univ., Beijing, China. Email: [email protected]

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