Clustering and Analysis of Maternal Mortality Causes in Rwanda: Implications for Targeted Health Interventions

Maternal mortality remains a critical public health challenge in Rwanda, with various factors contributing to adverse outcomes across different geographic regions. This study aimed to identify patterns and cluster mortality causes using Principal Component Analysis (PCA) and K-means clustering. K-means was chosen for its effectiveness in partitioning data into distinct, non-overlapping groups based on similarity of features, as well as its simplicity and scalability in handling multidimensional data. The analysis utilized a comprehensive dataset from the Civil Registration and Vital Statistics (CRVS) system, encompassing maternal death records in Rwanda. K-means clustering on the data revealed four distinct clusters characterized by unique patterns of causes of death, geographic distribution, and underlying conditions. The results highlighted the prevalence of post-partum hemorrhage in Cluster 1, the largest with 49 cases, showing high frequencies in Southern Province (14 cases), Western Province (12), and Kigali City (9). Cluster 2 (18 cases) focused on atonic postpartum hemorrhage, with a more even distribution across provinces. Pre-eclampsia superimposed on hypertension was prominent in Cluster 3, exclusively located in Kigali City (Nyarugenge district) with 11 cases. Geographical disparities were evident, with clusters showing varying concentrations in specific provinces and districts. Cluster 4 uniquely featured renal failure following unspecified abortion, with 15 cases spread across provinces but highest in Western Province (6 cases). The findings underscore the importance of tar-geted interventions, including enhanced medical training, focused healthcare programs, infrastructure improvements, community engagement, and data-driven strategic planning. By addressing the identified challenges through evidence-based approaches tailored to each cluster's specific characteristics, decision-makers can prioritize resources and develop targeted policies to improve maternal health outcomes across different regions in Rwanda.