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A spatiotemporal decay model of human mobility when facing large-scale crises

Author

Listed:
  • Weiyu Li

    (a School of Mathematical Sciences, Suzhou University of Science and Technology, Suzhou 215009, China;)

  • Qi Wang

    (b Department of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115;)

  • Yuanyuan Liu

    (c Lally School of Management, Rensselaer Polytechnic Institute, Troy, NY 12180;)

  • Mario L. Small

    (d Department of Sociology, Columbia University, New York, NY 10027;)

  • Jianxi Gao

    (e Department of Computer Science and NEST Center, Rensselaer Polytechnic Institute, Troy, NY 12180)

Abstract

Following large-scale extreme events—such as hurricanes, wildfires, and pandemics—changes in human movement patterns can vary dramatically from place to place and in the weeks and months following the event. Identifying patterns in spite of such variations across space and over time can help societies mount more effective responses. Our model uncovers that, across multiple types of events and despite their diversity and complexity, such changes follow a predictable hyperbolic pattern. The model can help understand and forecast movement patterns in future extreme events. It also uncovers hidden disparities in behavioral changes due to income inequality post large-scale crises.

Suggested Citation

  • Weiyu Li & Qi Wang & Yuanyuan Liu & Mario L. Small & Jianxi Gao, 2022. "A spatiotemporal decay model of human mobility when facing large-scale crises," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(33), pages 2203042119-, August.
    • Handle: RePEc:nas:journl:v:119:y:2022:p:e2203042119
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    Cited by:

    1. Gu, Xinyue & Chen, Pengyu & Fan, Chao, 2024. "Socio-demographic inequalities in the impacts of extreme temperatures on population mobility11This research received no specific grant from any funding agency, commercial or not-for-profit sectors," Journal of Transport Geography, Elsevier, vol. 114(C).

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