Assessing and Clustering Countries Based on COVID-19 and Related Indicators: Clustering and MULTIMOORA Approaches

Authors : Pakize Yıgıt

Pages : 876-896

Doi:10.35408/comuybd.1373504

View : 32 | Download : 32

Publication Date : 2024-07-22

Article Type : Research

Abstract :The COVID-19 pandemic has been one of humanity\'s most difficult times. The pandemic spread and impact were not at the same level for all countries. Investigation of the variation of the countries is crucial for policymakers. Therefore, the study proposed to cluster countries according to the number of COVID-19 cases, deaths, vaccinations and related socioeconomic, disease, and health risk factors and rank them by using MULTIMOORA (MOORA plus the full multiplicative form) in an integrated way. The data set consists of 148 countries and 13 indicators. K-Means algorithm was used to cluster countries. Optimal cluster was found as six according to Silhouette Index. The cluster consisted of mostly developed countries ranked as best perform cluster. It had the highest number of COVID-19 vaccinations, GDP per capita, share health expenditure in GDP, life expectancy, elderly population portion, and environmental performance index values, and the least mortality of chronic diseases. Moreover, Norway, Iceland, and Denmark were the best-performing countries in this cluster. In addition to this, Turkey was located in the second-ranked cluster. It was also determined that COVID-19 indicators (cases, deaths, and vaccinations) were related to GDP per capita, environmental index, and life expectancy. As a result, policymakers can develop pandemic policies for country groups separately, and assistance can be provided in this regard according to the priority order of the countries.
Keywords : COVID-19, kümeleme analizi, K-means, MULTIMOORA