IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i12p7146-d836045.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/12/7146/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/12/7146/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wei Liu & Xiao-Guang Yue & Paul B. Tchounwou, 2020. "Response to the COVID-19 Epidemic: The Chinese Experience and Implications for Other Countries," IJERPH, MDPI, vol. 17(7), pages 1-6, March.
    2. Zhang, Y. & Weng, W.G. & Huang, Z.L., 2018. "A scenario-based model for earthquake emergency management effectiveness evaluation," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 197-207.
    3. Gary Gereffi, 2020. "What does the COVID-19 pandemic teach us about global value chains? The case of medical supplies," Journal of International Business Policy, Palgrave Macmillan, vol. 3(3), pages 287-301, September.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Sajid Ullah & Farman Ullah Khan & Vanina Adoriana Trifan & Adina Eleonora Spinu & Grigorie Sanda, 2022. "Modeling Key Strategies for Reducing Socio-Economic and Health Crisis: Perspective from COVID-19 Pandemic," IJERPH, MDPI, vol. 19(21), pages 1-21, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiaojiao Qiao & Dan Shi, 2019. "Risk Analysis of Emergency Based on Fuzzy Evidential Reasoning," Complexity, Hindawi, vol. 2019, pages 1-10, November.
    2. Sajid Ullah & Farman Ullah Khan & Vanina Adoriana Trifan & Adina Eleonora Spinu & Grigorie Sanda, 2022. "Modeling Key Strategies for Reducing Socio-Economic and Health Crisis: Perspective from COVID-19 Pandemic," IJERPH, MDPI, vol. 19(21), pages 1-21, October.
    3. Jonathan H. Reed, 2022. "Operational and strategic change during temporary turbulence: evidence from the COVID-19 pandemic," Operations Management Research, Springer, vol. 15(1), pages 589-608, June.
    4. Grillitsch, Markus & Asheim, Björn & Fünfschilling, Lea & Kelmenson, Sophie & Lowe, Nichola & Lundquist, Karl Johan & Mahmoud, Yahia & Martynovich, Mikhail & Mattson, Pauline & Miörner, Johan & Nilsso, 2023. "Rescaling: An Analytical Lense to Study Economic and Industrial Shifts," Papers in Innovation Studies 2023/11, Lund University, CIRCLE - Centre for Innovation Research.
    5. Sarhadi, Hassan & Naoum-Sawaya, Joe & Verma, Manish, 2020. "A robust optimization approach to locating and stockpiling marine oil-spill response facilities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    6. Souza, Juliano Silva & Lim-Apo, Flávio Araújo & Varella, Leonardo & Coelho, Antônio Sérgio & Souza, João Carlos, 2022. "Multi-period optimization model for planning people allocation in shelters and distributing aid with special constraints," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    7. Massimiliano Scopelliti & Maria Giuseppina Pacilli & Antonio Aquino, 2021. "TV News and COVID-19: Media Influence on Healthy Behavior in Public Spaces," IJERPH, MDPI, vol. 18(4), pages 1-15, February.
    8. A. Anaya-Arenas & J. Renaud & A. Ruiz, 2014. "Relief distribution networks: a systematic review," Annals of Operations Research, Springer, vol. 223(1), pages 53-79, December.
    9. Roberta Capello & Andrea Caragliu, 2021. "Regional growth and disparities in a post‐COVID Europe: A new normality scenario," Journal of Regional Science, Wiley Blackwell, vol. 61(4), pages 710-727, September.
    10. Lu, Chung-Cheng & Ying, Kuo-Ching & Chen, Hui-Ju, 2016. "Real-time relief distribution in the aftermath of disasters – A rolling horizon approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 1-20.
    11. Wilson, Duncan T. & Hawe, Glenn I. & Coates, Graham & Crouch, Roger S., 2013. "A multi-objective combinatorial model of casualty processing in major incident response," European Journal of Operational Research, Elsevier, vol. 230(3), pages 643-655.
    12. Delera, Michele & Pietrobelli, Carlo & Calza, Elisa & Lavopa, Alejandro, 2022. "Does value chain participation facilitate the adoption of Industry 4.0 technologies in developing countries?," World Development, Elsevier, vol. 152(C).
    13. Kılcı, Fırat & Kara, Bahar Yetiş & Bozkaya, Burçin, 2015. "Locating temporary shelter areas after an earthquake: A case for Turkey," European Journal of Operational Research, Elsevier, vol. 243(1), pages 323-332.
    14. Christian M. Hafner, 2020. "The Spread of the Covid-19 Pandemic in Time and Space," IJERPH, MDPI, vol. 17(11), pages 1-13, May.
    15. Chassein, André & Goerigk, Marc & Kurtz, Jannis & Poss, Michael, 2019. "Faster algorithms for min-max-min robustness for combinatorial problems with budgeted uncertainty," European Journal of Operational Research, Elsevier, vol. 279(2), pages 308-319.
    16. Quddus, Md Abdul & Shahvari, Omid & Marufuzzaman, Mohammad & Ekşioğlu, Sandra D. & Castillo-Villar, Krystel K., 2021. "Designing a reliable electric vehicle charging station expansion under uncertainty," International Journal of Production Economics, Elsevier, vol. 236(C).
    17. Alem, Douglas & Clark, Alistair & Moreno, Alfredo, 2016. "Stochastic network models for logistics planning in disaster relief," European Journal of Operational Research, Elsevier, vol. 255(1), pages 187-206.
    18. Jill Juergensen & José Guimón & Rajneesh Narula, 2020. "European SMEs amidst the COVID-19 crisis: assessing impact and policy responses," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(3), pages 499-510, September.
    19. Zhao, Xian & Wang, Xinlei & Dai, Ying & Qiu, Qingan, 2024. "Joint optimization of loading, mission abort and rescue site selection policies for UAV," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    20. Das, Sanchita Basu & Sen, Rahul, 2022. "Trade Interdependencies in COVID-19-Related Essential Medical Goods: Role of Trade Facilitation and Cooperation for the Asian Economies," ADB Economics Working Paper Series 666, Asian Development Bank.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:12:p:7146-:d:836045. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.