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Evaluating the Effectiveness of the COVID-19 Emergency Outbreak Prevention and Control Based on CIA-ISM

Author

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  • Renlong Wang

    (Research Center of Smart City, Nanjing Tech University, Nanjing 211816, China
    College of Civil Engineering, Nanjing Tech University, Nanjing 211816, China)

  • Endong Wang

    (Department of Sustainable Resources Management, State University of New York, Syracuse, NY 13210, USA)

  • Lingzhi Li

    (Research Center of Smart City, Nanjing Tech University, Nanjing 211816, China
    College of Civil Engineering, Nanjing Tech University, Nanjing 211816, China)

  • Wei Li

    (Department of Construction and Real Estate, School of Civil Engineering, Southeast University, Nanjing 211189, China)

Abstract

The COVID-19 pandemic, characterized by high uncertainty and difficulty in prevention and control, has caused significant disasters in human society. In this situation, emergency management of pandemic prevention and control is essential to reduce the pandemic’s devastation and rapidly restore economic and social stability. Few studies have focused on a scenario analysis of the entire emergency response process. To fill this research gap, this paper applies a cross impact analysis (CIA) and interpretive structural modeling (ISM) approach to analyze emergency scenarios and evaluate the effectiveness of emergency management during the COVID-19 crisis for outbreak prevention and control. First, the model extracts the critical events for COVID-19 epidemic prevention and control, including source, process, and resultant events. Subsequently, we generated different emergency management scenarios according to different impact levels and conducted scenario deduction and analysis. A CIA-ISM based scenario modeling approach is applied to COVID-19 emergency management in Nanjing city, China, and the results of the scenario projection are compared with actual situations to prove the validity of the approach. The results show that CIA-ISM based scenario modeling can realize critical event identification, scenario generation, and evolutionary scenario deduction in epidemic prevention and control. This method effectively handles the complexity and uncertainty of epidemic prevention and control and provides insights that can be utilized by emergency managers to achieve effective epidemic prevention and control.

Suggested Citation

  • Renlong Wang & Endong Wang & Lingzhi Li & Wei Li, 2022. "Evaluating the Effectiveness of the COVID-19 Emergency Outbreak Prevention and Control Based on CIA-ISM," IJERPH, MDPI, vol. 19(12), pages 1-22, June.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:12:p:7146-:d:836045
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    References listed on IDEAS

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    4. Ziheng Shangguan & Mark Yaolin Wang & Wen Sun, 2020. "What Caused the Outbreak of COVID-19 in China: From the Perspective of Crisis Management," IJERPH, MDPI, vol. 17(9), pages 1-16, May.
    5. Chang, Mei-Shiang & Tseng, Ya-Ling & Chen, Jing-Wen, 2007. "A scenario planning approach for the flood emergency logistics preparation problem under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 737-754, November.
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    Cited by:

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    2. Yang, Zhen & Dong, Xiaobin & Guo, Li, 2023. "Scenario inference model of urban metro system cascading failure under extreme rainfall conditions," Reliability Engineering and System Safety, Elsevier, vol. 229(C).

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