Dengue Outbreak

Dengue fever outbreaks pose a significant global health challenge, demanding accurate prediction models to guide effective prevention and resource allocation. Current research heavily emphasizes the development and refinement of predictive models, utilizing diverse machine learning techniques such as convolutional neural networks (CNNs), transformers (including FWin transformers), and ensemble neural networks (like XEWNet), often incorporating meteorological data, satellite imagery, and entomological indices as input features. These advancements aim to improve forecast accuracy and reliability, particularly in resource-limited settings where data collection is challenging, ultimately supporting better public health interventions and reducing the disease burden.