How COVID-19 pandemic influenced the countries? A value at risk based fuzzy TOPSIS approach using IF–THEN rules

COVID-19 pandemic negatively affected healthcare in countries all over the world. When making support decisions related to reducing the pandemic's effects, government agencies should monitor various issues such as cumulative total cases, deaths, newly recorded case numbers, and their interactive effects on public health. The recovery policies used in the countries depend on the sufficient analysis of COVID-19 case-related daily data. The helpful big data sets are provided by the World Health Organization (WHO) day by day. In this paper, instead of using unique performance criteria, an overall performance score is calculated for a selected country in the world using the fuzzy TOPSIS method. We use various attributes to determine which countries are most negatively impacted by the COVID-19 pandemic. We illustrate the applicability of the developed decision support framework in this paper. The fuzzy TOPSIS approach developed in this paper has many primary benefits. For example, we can determine the level of influence of the COVID-19 pandemic for an individual country. Another advantage of the fuzzy TOPSIS approach is that it allows for the comparison of the local, rather than ignoring the population effect, country-wide impact of the COVID-19 pandemic with that of other countries. In the modeling stage, we incorporate the Value at Risk (VaR) integrated IF–Then rules to convert the cognitive evaluation of the criteria weights by the decision maker to the corresponding fuzzy numbers. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.