Satellite-based AI for climate-driven dengue prediction in Bangladesh: A literature review

This literature review explores the use of satellite-based artificial intelligence (AI) models for climate-driven dengue prediction in Bangladesh. Dengue outbreaks are significantly influenced by climatic factors such as temperature, rainfall, and humidity, which can be effectively monitored using satellite remote sensing data. The study synthesizes findings from existing research on integrating climate variables with AI and machine learning algorithms for early warning and outbreak forecasting. Emphasis is placed on the potential of satellite imagery, big data analytics, and predictive modeling to enhance public health surveillance, reduce the burden of dengue, and support decision-making for vector control. The review also highlights key challenges, including data availability, model generalization, and the need for interdisciplinary collaboration to improve prediction accuracy.