AI-Driven Dengue Prediction and Risk Management System

Dengue fever remains a significant public health threat, with outbreaks intensifying in tropical and subtropical regions globally. Traditional surveillance methods often struggle to predict and mitigate these outbreaks effectively. This paper proposes an AI-based predictive model and risk management system for identifying and responding to dengue outbreak conditions. By analyzing key factors, such as climate conditions, environmental attributes, and socio-geographical characteristics, the proposed system classifies regions based on outbreak risk and alerts communities about potential dengue risks. Using cloud-based services, this system integrates real-time data to generate interactive heatmaps, regional alerts, and preventive guidelines for subscribers. The system also offers region-specific hospital recommendations, aiming to enhance preparedness and minimize outbreak impact. This approach presents a proactive solution for public health agencies and local communities to combat dengue through targeted, data-driven interventions.