Dengue Early Warning System and Outbreak Prediction Tool in Bangladesh Using Interpretable Tree-Based Machine Learning Model.
Journal:
Health science reports
Published Date:
May 1, 2025
Abstract
BACKGROUND AND AIMS: A life-threatening vector-borne disease, dengue fever (DF), poses significant global public health and economic threats, including Bangladesh. Determining dengue risk factors is crucial for early warning systems to forecast disease epidemics and develop efficient control strategies. To address this, we propose an interpretable tree-based machine learning (ML) model for dengue early warning systems and outbreak prediction in Bangladesh based on climatic, sociodemographic, and landscape factors.
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