Different Variants of Pandemic and Prevention Strategies: A Prioritizing Framework in Fuzzy Environment

Abstract

In this trying time for the world battling different variants of the COVID-19 pandemic, government intervention strategies are being taken to limit the spread of infection. Closing educational institutes, stay-at-home orders, campaigns for emphasis on vaccination, the usage of medical masks, and frequently sanitizing hands etc. are the endeavors made by the authorities to decrease the number of cases in the country. In this regard, the contribution aims to help the decision-makers identify a potential prevention strategy based on public acceptance and intervention effectiveness. To achieve this objective, feasible judgments of professionals from three different sectors are brought together through meetings. Opinions, based on ten criteria, are recorded in linguistic form to prioritize six alternatives. The linguistic terms are then evaluated and manipulated by entailing triangular fuzzy numbers and a group multi-criteria decision making (GMCDM) approach. Consequently, through the ranking orders of defuzzified scores, an intuitive preference for compromise solutions is suggested. This comparative study is carried out through the technique for order of preference by similarity to ideal solution (TOPSIS), which produces the same preference for alternatives. In addition, this strategy can be discovered to be an effective strategy adopted by different countries in successfully decreasing the number of cases