Unveiling Mortality Patterns in Ecuador: A K-Modes Clustering Approach to Categorical Data Analysis

This study applies the k-modes clustering algorithm to analyze mortality in Ecuador, utilizing categorical data to reveal patterns related to demographic factors and causes of death. We identify distinct mortality profiles by carefully preprocessing a comprehensive dataset to focus on critical variables such as age and province of death. Our analysis uncovers significant disparities in mortality rates driven by socioeconomic and regional influences. These findings highlight the demographic and geographical factors affecting mortality and provide essential insights for public health officials and policymakers to develop targeted interventions. This research significantly advances epidemiological studies, offering a novel perspective on Ecuador’s mortality trends and guiding healthcare policy and resource distribution. We discuss the study’s limitations and future research directions, emphasizing the importance of ongoing analysis to improve public health strategies. This effort seeks to bolster the efficacy of health interventions and policies, striving for a meaningful improvement in public health in Ecuador.