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Assessment of monthly economic losses in Wuhan under the lockdown against COVID-19

Author

Listed:
  • Shibing You

    (Wuhan University)

  • Hengli Wang

    (Wuhan University)

  • Miao Zhang

    (Wuhan University)

  • Haitao Song

    (Shanxi University)

  • Xiaoting Xu

    (Wuhan University)

  • Yongzeng Lai

    (Wilfrid Laurier University)

Abstract

With the outbreak of COVID-19 in Wuhan, aggressive countermeasures have been taken, including the implementation of the unprecedented lockdown of the city, which will necessarily cause huge economic losses for the city of Wuhan. In this paper, we attempt to uncover the interactions between epidemic prevention and control measures and economic-social development by estimating the health loss and meso-economic loss from a human-oriented perspective. We implemented a compartmental model for the transmission dynamics and health burden assessment to evaluate the health losses, then estimated the direct and indirect economic losses of industries using the Input-Output model. Based on these estimates, the first monthly health losses and meso-economic losses caused by the lockdown was assessed. The overall policy effect of the lockdown policy in Wuhan was also investigated. The health loss and meso-economic losses are used to evaluate the health burden and loss of residents’ mental health, the direct economic loss of several worst-hit industries, and the indirect economic loss of all industries, respectively. Our findings reveal that the health burden caused by this pandemic is estimated to be 4.4899 billion yuan (CNY), and the loss of residents’ mental health is evaluated to be 114.545 billion yuan, the direct economic losses in transport, logistics, and warehousing, postal service, food, and beverage service industries reach 21.6094 billion yuan, and the monthly indirect economic losses of all industries are 36.39661994 billion yuan caused by the lockdown. The total monthly economic losses during the lockdown reach 177.0413 billion yuan. However, the lockdown policy has been considered to reduce COVID-19 infections by >180 thousand, which saves about 20 thousand lives, as well as nearly 30 billion yuan on medical costs. Therefore, the lockdown policy in Wuhan has obvious long-term benefits on the society and the total economic losses will be at a controllable level if effective measures are taken to combat COVID-19.

Suggested Citation

  • Shibing You & Hengli Wang & Miao Zhang & Haitao Song & Xiaoting Xu & Yongzeng Lai, 2020. "Assessment of monthly economic losses in Wuhan under the lockdown against COVID-19," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-12, December.
    • Handle: RePEc:pal:palcom:v:7:y:2020:i:1:d:10.1057_s41599-020-00545-4
    DOI: 10.1057/s41599-020-00545-4
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    References listed on IDEAS

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    Cited by:

    1. Wang, Peipei & Liu, Haiyan & Zheng, Xinqi & Ma, Ruifang, 2023. "A new method for spatio-temporal transmission prediction of COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    2. Xingtian Chen & Wei Gong & Xiaoxu Wu & Wenwu Zhao, 2021. "Estimating Economic Losses Caused by COVID-19 under Multiple Control Measure Scenarios with a Coupled Infectious Disease—Economic Model: A Case Study in Wuhan, China," IJERPH, MDPI, vol. 18(22), pages 1-19, November.
    3. Cui, Zhiwei & Fu, Xin & Wang, Jianwei & Qiang, Yongjie & Jiang, Ying & Long, Zhiyou, 2022. "How does COVID-19 pandemic impact cities' logistics performance? An evidence from China's highway freight transport," Transport Policy, Elsevier, vol. 120(C), pages 11-22.
    4. Zhou, Lijuan & Zhang, Ruchuan & Zhang, Aizhen & Li, Miao & Li, Aijun, 2024. "Understanding the role of energy sector in the outbreak of epidemic in China: An analysis based on SEIDR epidemic model, dynamic input-output model and resource allocation DEA model," Energy, Elsevier, vol. 305(C).
    5. Tong Li & Yanfen Wang & Lizhen Cui & Ranjay K. Singh & Hongdou Liu & Xiufang Song & Zhihong Xu & Xiaoyong Cui, 2023. "Exploring the evolving landscape of COVID-19 interfaced with livelihoods," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    6. Fu, Xin & Qiang, Yongjie & Liu, Xuxu & Jiang, Ying & Cui, Zhiwei & Zhang, Deyu & Wang, Jianwei, 2022. "Will multi-industry supply chains' resilience under the impact of COVID-19 pandemic be different? A perspective from China's highway freight transport," Transport Policy, Elsevier, vol. 118(C), pages 165-178.
    7. Yagi, Michiyuki & Managi, Shunsuke, 2021. "Global supply constraints from the 2008 and COVID-19 crises," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 514-528.

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