aspg-28-4122-1792155152 20261016125232 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Artificial Intelligence and Metaheuristics JAIM 2833-5597 2025 10 2 Noor Razzaq Abbas Al-Furat Al-Awsat Technical University, Technical Institute of Najaf, Najaf, Iraq Ghassan AL-Thabhawee Sciences of Mathematics, Computer Sciences, College of Health and Medical Techniques-Kufa, Al-Furat Al-Awsat Technical University, Kufa, Iraq Isam Bahaa Aldallal Department of Electrical and Computer Engineering, Altinbas University, Istanbul, Turkey Mostafa Abotaleb Engineering School of Digital Technologies, Yugra State University, Khanty-Mansiysk, 628012, Russia Klodian Dhoska Department of Production and Management, Polytechnic University of Tirana, 1001, Tirana, Albania Hierarchical clustering is applied to global COVID-19 data from the Worldometer tracker, whose final update was April 13, 2024, to partition countries into clusters based on epidemiological indicators. Total cases, deaths, recoveries, active cases, tests, population, and per-million measures are standardized and analyzed using agglomerative hierar-chical clustering with Ward linkage. The evaluation yields an average Silhouette score of 38.5%, a Davies–Bouldin value of 0.87, and a Calinski–Harabasz value of 77.6. Dendrograms and principal component analysis (PCA) projections identify four clusters, reflecting differences in pandemic impact and response. The analysis finds that high-burden clusters account for almost 45% of global deaths, while low-burden clusters predominate in more than 40% of nations with fewer than 100,000 accumulated cases. The results illustrate how hierarchical clustering can support comparative public-health analysis by providing quantitative estimates of epidemiological patterns across countries. 2025 09 14 4122 https://creativecommons.org/licenses/by/4.0/ 10.54216/JAIM.100202 https://www.americaspg.com/journal/28/article/4122 https://www.americaspg.com/storage/articles/manuscripts/01M4J4M44B980AVZQDH76E0C4V.pdf