Abstract To verify the effects of Wuhan highway lockdown measures on the spread of COVID-19 across China cities, we extracted the vehicle outflow from Wuhan to 245 cities from the Chinese highway toll system. A dynamic exponential risk model that considered the vehicle outflow, city gross domestic product, city population, and distance between two cities was established to characterize the spread of pandemics and quantify the blocking effects. Results showed that an early highway lockdown measure could indeed reduce the confirmed cases and vehicles with 1–9 seats played a leading role. The confirmed cases in Guangxi, Henan, and Shanxi could be reduced by more than 50%, as well as Hubei by 20% if the highway was closed 3 days in advance. The blocking effects on Fujian, Jiangxi, Guangdong, Hunan, and Shandong were not obvious, where the number of confirmed cases only decreased by a small proportion (below 10%). The findings could be used to help each provincial government to adjust policies properly and improve the effectiveness of epidemic control and prevention. Moreover, the proposed method could also be applied to various countries or regions affected by COVID-19, as well as other similar pandemics.

    Highlights Using highway toll system data to study the epidemic spread. Observing impacts of Wuhan highway lockdown measures and different vehicle types on the epidemic spread in China. Exploring key factors of epidemic spread in different provinces and regions of China. Proposing policy recommendations for the prevention of epidemic spread.


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    Title :

    The effects of Wuhan highway lockdown measures on the spread of COVID-19 in China


    Contributors:
    Meng, Xin (author) / Guo, Mingxue (author) / Gao, Ziyou (author) / Yang, Zhenzhen (author) / Yuan, Zhilu (author) / Kang, Liujiang (author)

    Published in:

    Transport Policy ; 117 ; 169-180


    Publication date :

    2022-01-17


    Size :

    12 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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