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Dynamic governance decisions on multi-modal inter-city travel during a large-scale epidemic spreading

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  • An, Yunlong
  • Lin, Xi
  • Li, Meng
  • He, Fang

Abstract

Within half a year, COVID-19 spreads to most countries in the world, as well as posed a great threat to the public health of human beings. The implementation of non-pharmaceutical intervention (NPI), including travel ban, proved to be an effective way for controlling the epidemic spreading, e.g., the ban of inter-city transportation stops transporting virus through passengers between cities. However, travel ban could significantly impact many industries, e.g. tourism and logistics, thus jeopardizing the regional economy. This paper focus on assisting the national or regional government to make dynamic decisions on restricting and recovering intercity multi-modal travel services. Our model can characterize impacts of inter-city traffic on the spread of the COVID-19, as well as on the regional economy. By applying a reinforcement learning approach, we develop an online optimization model to identify the modal-specific travel banning strategy that can balance the epidemic control as well as the negative impacts on regional economy. The numerical study based on a network of multiple cities in China shows that the proposed approach can generate better strategies compared with some existing methods.

Suggested Citation

  • An, Yunlong & Lin, Xi & Li, Meng & He, Fang, 2021. "Dynamic governance decisions on multi-modal inter-city travel during a large-scale epidemic spreading," Transport Policy, Elsevier, vol. 104(C), pages 29-42.
    • Handle: RePEc:eee:trapol:v:104:y:2021:i:c:p:29-42
    DOI: 10.1016/j.tranpol.2021.01.008
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    References listed on IDEAS

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    1. Beck, Matthew J. & Hensher, David A., 2022. "Australia 6 months after COVID-19 restrictions- part 1: Changes to travel activity and attitude to measures," Transport Policy, Elsevier, vol. 128(C), pages 286-298.
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    3. Tao Lian & Shamsheer ul Haq & Pomi Shahbaz & Lei Zhao & Muhammad Nadeem & Babar Aziz, 2022. "Changing Food Patterns during the Pandemic: Exploring the Role of Household Dynamics and Income Stabilization Strategies," Sustainability, MDPI, vol. 15(1), pages 1-20, December.
    4. 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.
    5. Zha, Wenbin & Ye, Qian & Li, Jian & Ozbay, Kaan, 2023. "A social media Data-Driven analysis for transport policy response to the COVID-19 pandemic outbreak in Wuhan, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 172(C).

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