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Abstract

This study examines the correlation between political leanings and COVID-19 mortality across the states of America affiliated with Republican and Democratic governance. Employing emergent self-organizing map (ESOM), cluster analysis, and the logistic classification, we group states based on COVID-19 properties, identify risk patterns, and assess risk levels. Factors considered include poverty rate, education rate, vaccination rate, and demographics. The Logistic Algorithm succinctly summarizes findings, integrating ESOM, cluster analysis, and logistic classification results. This multi-method approach aims to offer a concise, yet comprehensive understanding of the COVID-19 risk landscape in politically diverse states, shedding light on potential associations between political affiliations and pandemic outcomes.

*This article was published as part of the Proceedings of the 16th Symposium on BEER and reviewed for editorial clarity only.

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