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A dynamic physical-distancing model to evaluate spatial measures for prevention of Covid-19 spread

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  • Xiao, Tianyi
  • Mu, Tong
  • Shen, Sunle
  • Song, Yiming
  • Yang, Shufan
  • He, Jie

Abstract

Motivated by the global pandemic of COVID-19, this study investigates the spatial factors influencing physical distancing, and how these affect the transmission of the SARS-CoV-2 virus, by integrating pedestrian dynamics with a modified susceptible–exposed–infectious model. Contacts between infected and susceptible pedestrians are examined by determining physical-distancing pedestrian dynamics in three types of spaces, and used to estimate the proportion of newly infected pedestrians in these spaces. Desired behaviour for physical distancing can be observed from simulation results, and aggregated simulation findings reveal that certain layouts enable physical distancing to reduce the transmission of SARS-CoV-2. We also provide policymakers with several design guidelines on how to proactively design more effective and resilient space layouts in the context of pandemics to keep low transmission risks while maintaining a high pedestrian volume. This approach has enormous application potential for other infectious-disease transmission and space assessments.

Suggested Citation

  • Xiao, Tianyi & Mu, Tong & Shen, Sunle & Song, Yiming & Yang, Shufan & He, Jie, 2022. "A dynamic physical-distancing model to evaluate spatial measures for prevention of Covid-19 spread," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    • Handle: RePEc:eee:phsmap:v:592:y:2022:i:c:s0378437121009390
    DOI: 10.1016/j.physa.2021.126734
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    1. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    2. Suma, Yushi & Yanagisawa, Daichi & Nishinari, Katsuhiro, 2012. "Anticipation effect in pedestrian dynamics: Modeling and experiments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 248-263.
    3. Sullivan, Joe H. & Warkentin, Merrill & Wallace, Linda, 2021. "So many ways for assessing outliers: What really works and does it matter?," Journal of Business Research, Elsevier, vol. 132(C), pages 530-543.
    4. Caspar A S Pouw & Federico Toschi & Frank van Schadewijk & Alessandro Corbetta, 2020. "Monitoring physical distancing for crowd management: Real-time trajectory and group analysis," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-18, October.
    5. Pierrot Derjany & Sirish Namilae & Dahai Liu & Ashok Srinivasan, 2020. "Multiscale model for the optimal design of pedestrian queues to mitigate infectious disease spread," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-21, July.
    6. Yuan Liu & Zhi Ning & Yu Chen & Ming Guo & Yingle Liu & Nirmal Kumar Gali & Li Sun & Yusen Duan & Jing Cai & Dane Westerdahl & Xinjin Liu & Ke Xu & Kin-fai Ho & Haidong Kan & Qingyan Fu & Ke Lan, 2020. "Aerodynamic analysis of SARS-CoV-2 in two Wuhan hospitals," Nature, Nature, vol. 582(7813), pages 557-560, June.
    7. Ruth F. Hunter & Leandro Garcia & Thiago Herick Sa & Belen Zapata-Diomedi & Christopher Millett & James Woodcock & Alex ’Sandy’ Pentland & Esteban Moro, 2021. "Effect of COVID-19 response policies on walking behavior in US cities," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    8. Parisi, Daniel R. & Gilman, Marcelo & Moldovan, Herman, 2009. "A modification of the Social Force Model can reproduce experimental data of pedestrian flows in normal conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3600-3608.
    9. Dirk Helbing & Lubos Buzna & Anders Johansson & Torsten Werner, 2005. "Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions," Transportation Science, INFORMS, vol. 39(1), pages 1-24, February.
    10. Han, Yanbin & Liu, Hong, 2017. "Modified social force model based on information transmission toward crowd evacuation simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 499-509.
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