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Connecting urban transportation systems with the spread of infectious diseases: A Trans-SEIR modeling approach

Author

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  • Qian, Xinwu
  • Ukkusuri, Satish V.

Abstract

Urban transportation systems satisfy the essential mobility needs of the large-scale urban population, but it also creates an ideal environment that favors the spread of infectious diseases, leading to significant risk exposure to the massive urban population. In this study, we develop the mathematical model to understand the coupling between the spreading dynamics of infectious diseases and the mobility dynamics through urban transportation systems. We first describe the mobility dynamics of the urban population as the process of leaving from home, traveling to and from the activity locations, and engaging in activities. We then embed the susceptible-exposed-infectious-recovered (SEIR) process over the mobility dynamics and develops the spatial SEIR model with travel contagion (Trans-SEIR), which explicitly accounts for contagions both during travel and during daily activities. We investigate the theoretical properties of the proposed model and show how activity contagion and travel contagion contribute to the average number of secondary infections. We further develop an optimal control strategy for the effective entrance control of public transportation systems with optimal allocation of limited resources. In the numerical experiments, we explore how the urban transportation system may alter the fundamental dynamics of the infectious disease, change the number of secondary infections, promote the synchronization of the disease across the city, and affect the peak of the disease outbreaks. The Trans-SEIR model is further applied to understand the disease dynamics during early COVID-19 outbreak in New York City, where we show how the activity and travel contagion may be distributed and how effective entrance control can be implemented in urban transportation systems. The Trans-SEIR model, along with the findings in our study, may significantly improve our understanding of the coupling between urban transportation systems and disease dynamics, the development of quarantine and control measures for mitigating the disease risks and promoting the idea of disease-resilient urban transportation networks.

Suggested Citation

  • Qian, Xinwu & Ukkusuri, Satish V., 2021. "Connecting urban transportation systems with the spread of infectious diseases: A Trans-SEIR modeling approach," Transportation Research Part B: Methodological, Elsevier, vol. 145(C), pages 185-211.
    • Handle: RePEc:eee:transb:v:145:y:2021:i:c:p:185-211
    DOI: 10.1016/j.trb.2021.01.008
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    Citations

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    Cited by:

    1. Zheng, Hongyu & Zhang, Kenan & Nie, Yu (Marco), 2021. "Plunge and rebound of a taxi market through COVID-19 lockdown: Lessons learned from Shenzhen, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 349-366.
    2. Elif Bozkaya & Levent Eriskin & Mumtaz Karatas, 2023. "Data analytics during pandemics: a transportation and location planning perspective," Annals of Operations Research, Springer, vol. 328(1), pages 193-244, September.
    3. Jiang, Jiehui & Ma, Jie, 2023. "Dynamic analysis of pandemic cross-regional transmission considering quarantine strategies in the context of limited medical resources," Applied Mathematics and Computation, Elsevier, vol. 450(C).
    4. Nie, Qifan & Qian, Xinwu & Guo, Shuocheng & Jones, Steven & Doustmohammadi, Mehrnaz & Anderson, Michael D., 2022. "Impact of COVID-19 on paratransit operators and riders: A case study of central Alabama," Transportation Research Part A: Policy and Practice, Elsevier, vol. 161(C), pages 48-67.
    5. Lu, Zhong-Wen & Xu, Yuan-Hao & Chen, Jie & Hu, Mao-Bin, 2023. "Investigation of traffic-driven epidemic spreading by taxi trip data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    6. Li, Siping & Zhou, Yaoming & Kundu, Tanmoy & Sheu, Jiuh-Biing, 2021. "Spatiotemporal variation of the worldwide air transportation network induced by COVID-19 pandemic in 2020," Transport Policy, Elsevier, vol. 111(C), pages 168-184.
    7. Liu, Shasha & Yamamoto, Toshiyuki, 2022. "Role of stay-at-home requests and travel restrictions in preventing the spread of COVID-19 in Japan," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 1-16.

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