Dengue Risk Mapping in Sri Lanka Using Spatial Interpolation, Machine Learning, and Ensemble Modeling
This study develops an integrated framework combining Ordinary Kriging, Random Forest, and Multi-Layer Perceptron models to create district-level dengue risk maps in Sri Lanka, demonstrating that this ensemble approach effectively identifies high-risk urban areas and supports targeted public health interventions.