Enhancing Disease Surveillance and Epidemiological Forecasting with AI and Big Data Analytics

Abstract

This research paper explores the potential of AI and big data analytics in enhancing disease surveillance and epidemiological forecasting. By leveraging diverse data sources, including electronic health records, social media feeds, and environmental sensors, our approach enables early detection of disease outbreaks, tracking of disease transmission dynamics, and forecasting of disease trends at local, regional, and global scales. Implementation of these methods can strengthen public health preparedness, facilitate timely interventions, and mitigate the impact of infectious diseases on population health.