Modeling diarrhea in children under five in Somaliland: A machine learning analysis using SLDHS 2020 data

Diarrhea remains a leading cause of morbidity and mortality among children under five years of age, particularly in low- and middle-income countries. This study investigated the prevalence and determinants of diarrhea in Somaliland using nationally representative data from the Somaliland Health and Demographic Survey (SLDHS) 2020. The study employed machine learning algorithms, including Random Forest and XGBoost, to analyze factors contributing to the disease. Results showed a prevalence of 18.5%. The most significant predictors identified were the child's age, maternal education level, source of drinking water, type of toilet facility, and household wealth index. The findings emphasize the need for targeted interventions in water, sanitation, and hygiene (WASH) infrastructure and maternal education to reduce the burden of diarrheal diseases.