AI-Driven Dengue Outbreak Prediction and Early Warning System

Abstract

Dengue fever continues to be a significant public health issue in Pakistan, mostly seen in cities like Lahore and Karachi, which face yearly outbreaks that put pressure on healthcare systems. Being able to predict these outbreaks in advance can facilitate timely interventions, minimize disease spread, and enhance resource allocation for public health officials. This project seeks to create a data-driven predictive model for forecasting dengue outbreaks by utilizing public health data, weather trends, population density, and geospatial analysis. which incorporates machine learning methods such as time-series forecasting and by utilizing datasets from opensource portals and climate data sources, the system will pinpoint high risk areas and provide warnings. Furthermore, a geospatial analysis module will be included to visualize regions and their probable dengue cases using GIS tools and heatmaps. A trained chatbot will also be developed to propose preventive measures. To enhance public health awareness and timely interventions an automated alert notification system will inform users when they enter certain high-risk areas about potential outbreak threats. The system will be accessible by an interactive dashboard and a mobile application to provide easy accessibility and a hands on user experience which will enable users to track dengue trends and implement proactive measures. In addition to dengue case predicitons, the system emphasizes awareness through an intelligent, multi-platform interface. The integration of real-time risk mapping, Firebase powered push notifications, and a chatbot based on precautions which ensures that users receive personalized and timely information to make informed health decisions. By combining AI driven forecasting, GIS, and communication technologies, this project aims not only to support proactive dengue management but also to contribute toward the development of a scalable framework for digital disease surveillance in Pakistan.