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Supply chain loss from easing COVID-19 restrictions: an evolutionary economic-epidemiological modelling study

  • Yang Ye
  • , Zhidong Cao
  • , Daniel Dajun Zeng
  • , Qingpeng Zhang

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

23 Downloads (CityUHK Scholars)

Abstract

Since the start of the COVID-19 pandemic, many firms have been shifting their supply chains away from countries with stringent control measures to mitigate supply-chain disruption. Nowadays, the global economy has reopened from the COVID-19 pandemic at various paces in different countries. Understanding how the global supply network evolves during and after the pandemic is necessary for determining the timing and speed of reopening. By harnessing the real-world and real-time global human movement and the latest macroeconomic data, we propose an evolutionary economic-epidemiological model to explore the evolutionary dynamics of the global supply network under various global reopening scenarios. We find that, for highly restrictive countries, the delay in reopening has limited public health benefits in the long run but leads to significant supply-chain loss. A longer duration of stringent control measures substantially hurts the profitability of firms in highly restrictive countries, leading to slower supply-chain recovery in 5 years. This research presents the first data-driven evidence of supply chain loss due to the timing and speed of reopening and sheds light on the post-pandemic supply-chain reformation and recovery. Insights learned from COVID-19 will also be a valuable policymaking reference for combating future infectious disease epidemics and geopolitical changes. © 2024 Royal Society Publishing. All rights reserved.
Original languageEnglish
Article number0803
JournalProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
Volume480
Issue number2283
Online published7 Feb 2024
DOIs
Publication statusPublished - Feb 2024
Externally publishedYes

Funding

This work was supported in part by the National Natural Science Foundation of China (Grant Nos. 71972164, 72293575, and 72025404) and in part by the Research Grants Council of the Hong Kong Special Administrative Region, China (Grant Nos. 11218221, C7154-20GF, C7151-20GF, and C1143-20GF).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Research Keywords

  • COVID-19
  • evolutionary dynamics
  • supply chains

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

RGC Funding Information

  • RGC-funded

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