An integrated data-driven approach for Chronic Kidney Disease of Unknown Etiology (CKDu) risk profiling and prediction in Sri Lanka

Abstract

Chronic kidney disease of unknown etiology is a significant public health issue in Sri Lanka, especially in rural farming communities. The exact causes remain unclear, with potential links to environmental and socio-economic factors. This research employs Biological Data and Geographic Information Systems to analyze risk factors such as water quality, agricultural practices, climatic conditions, Demographic Factors, Socio-economic Factors. This study uses data from government health records, the Centre for Research-National Hospital Kandy, and field surveys. By identifying patterns and correlations, the study aims to inform public health interventions and reduce the impact of CKDu, ultimately improving health outcomes for affected populations. This will greatly contribute to preventing the disease, reducing the risk, and identifying patients at an early stage.