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Decision-making framework for identifying regions vulnerable to transmission of COVID-19 pandemic

Gupta, Rohit, Rathore, Bhawana, Srivastava, Abhishek and Biswas, Baidyanath orcid logoORCID: 0000-0002-0609-3530 (2022) Decision-making framework for identifying regions vulnerable to transmission of COVID-19 pandemic. Computers & Industrial Engineering, 169 . ISSN 0360-8352

Abstract At the beginning of 2020, the World Health Organization (WHO) identified an unusual coronavirus and declared the associated COVID-19 disease as a global pandemic. We proposed a novel hybrid fuzzy decision-making framework to identify and analyze these transmission factors and conduct proactive decision-making in this context. We identified thirty factors from the extant literature and classified them into six major clusters (climate, hygiene and safety, responsiveness to decision-making, social and demographic, economic, and psychological) with the help of domain experts. We chose the most relevant twenty-five factors using the Fuzzy Delphi Method (FDM) screening from the initial thirty. We computed the weights of those clusters and their constituting factors and ranked them based on their criticality, applying the Fuzzy Analytic Hierarchy Process (FAHP). We found that the top five factors were global travel, delay in travel restriction, close contact, social cohesiveness, and asymptomatic. To evaluate our framework, we chose ten different geographically located cities and analyzed their exposure to COVID-19 pandemic by ranking them based on their vulnerability of transmission using Fuzzy Technique for Order of Preference by Similarity To Ideal Solution (FTOPSIS). Our study contributes to the discipline of decision analytics and healthcare risk management during a pandemic through these novel findings. Policymakers and healthcare officials can also benefit from our study by formulating and improving existing preventive measures to mitigate future global pandemics. Finally, we performed a sequence of sensitivity analyses to check for the robustness and generalizability of our proposed hybrid decision-making framework. Keywords: COVID-19; Epidemic transmission; Fuzzy Decision framework; Fuzzy Delphi;
Item Type:Article (Published)
Additional Information:Article number: 108207
Uncontrolled Keywords:COVID-19; Epidemic transmission; Fuzzy Decision framework; Fuzzy Delphi; Fuzzy A.H.P.; Fuzzy TOPSIS
Subjects:Business > Economic policy
Business > Management
Medical Sciences > Epidemiology
DCU Faculties and Centres:DCU Faculties and Schools > DCU Business School
Official URL:https://doi.org/10.1016/j.cie.2022.108207
Copyright Information:© 2022 Elsevier.
ID Code:27379
Deposited On:22 Jul 2022 13:40 by Baidyanath Biswas . Last Modified 08 Mar 2023 10:36

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