Identification of dominant risk factor involved in spread of COVID-19 using hesitant fuzzy MCDM methodology

The outburst of the pandemic Coronavirus disease since December 2019, has severely impacted the health and economy worldwide. The epidemic is spreading fast through various means, as the virus is very infectious. Medical science is exploring a vaccine, only symptomatic treatment is possible at the moment. To contain the virus, it is required to categorize the risk factors and rank those in terms of contagion. This study aims to evaluate risk factors involved in the spread of COVID-19 and to rank them. In this work, we applied the methodology namely, Fuzzy Analytic Hierarchy Process (FAHP) to find out the weights and finally Hesitant Fuzzy Sets (HFS) with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to identify the major risk factor. The results showed that long duration of contact with the infected person the most significant risk factor, followed by spread through hospitals and clinic and verbal spread. We showed the appliance of the Multi Criteria Decision Making (MCDM) tools in evaluation of the most significant risk factor. Moreover, we conducted sensitivity analysis.

Automated summary

The outbreak of the COVID-19 pandemic since December 2019 has significantly impacted global health and economy. To contain the virus, evaluating and ranking risk factors is crucial. This study utilized the FAHP methodology to determine weights and applied HFS with TOPSIS to identify the major risk factor as prolonged contact with infected individuals, spread through hospitals and clinics, and verbal transmission. The research demonstrated the application of MCDM tools for evaluating the most significant risk factor and conducted a sensitivity analysis.