A Probabilistic Hesitant Fuzzy MCDM Approach to Selecting Treatment Policy For COVID-19

Abstract

The global significant rise in the number of sick individuals and fatalities has made the ongoing struggle against the severe and lethal COVID-19 pandemic a global effort. There are several ongoing therapies for COVID-19, and more are being developed. However, selecting the best therapy option for COVID-19 patients is still needed. Patients may easily choose from the available COVID-19 therapies using the multi-criteria decision-making method. As a result, the present study provides an MCDM method that is created to determine COVID-19 therapies. Probabilistic Hesitant Fuzzy Set numbers, values, and ambiguity are introduced. Theorems and characteristics of PHFS numbers are also investigated in depth. The Complex Proportional Assessment technique is used, based on the PHFS, for dealing with ambiguity issues. This study uses ten criteria and three treatment methods: antibacterial medication and plasma treatment, vaccinations, as well as quarantine and in-house isolation. The study results reveal that quarantine and isolation at home mark the most effective treatment, followed by vaccinations with antibiotics and plasma therapy.