Pandemic Predict - Epidemic Spread Forecasting using Machine Learning Algorithms and Population Data with Predictive Analytics

Abstract

Pandemic Predict is an intelligent epidemic forecasting system that leverages machine learning algorithms and population data to analyze and predict the spread of infectious diseases. The system integrates diverse datasets, including demographic information, mobility patterns, environmental factors, and historical health records, to build accurate predictive models. Advanced techniques such as time-series forecasting, regression, and deep learning are used to identify patterns and trends in disease transmission. The model continuously learns from real-time data, improving its prediction accuracy over time. It also incorporates geospatial analysis to detect high-risk regions and visualize outbreak hotspots. The system provides early warnings and actionable insights to support timely decision-making by healthcare authorities and governments. By automating data analysis and forecasting, it reduces manual effort and enhances efficiency. The proposed solution aims to improve pandemic preparedness, resource allocation, and response strategies. Overall, it offers a scalable, adaptive, and data-driven approach to epidemic spread prediction.