Hydro-Climatic Spatio -Temporal Dengue Risk Prediction System

Abstract: This paper presents an integrated health informatics framework aimed at forecasting and mitigating dengue outbreaks by fusing hydro-climatic conditions with symptom-based user inputs. The proposed system evaluates environmental variables—namely rainfall, temperature, and humidity—alongside self-reported symptoms and historical disease trends to estimate the likelihood of dengue transmission across different regions. By implementing rule-based logic and leveraging spatio-temporal analysis, the system offers real-time risk estimations and context-specific preventive guidance. Key features include a symptom evaluation tool, geo-based alert notifications, and a risk scoring mechanism derived from user questionnaires. The interface also incorporates visual elements such as dynamic heatmaps and time-series charts to enhance public understanding and actionable response. Developed with usability and public health relevance in mind, this platform serves as a practical and scalable tool to support early intervention strategies against vector-borne diseases like dengue