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Track 25: Digital Epidemiology and AI-Based Disease Forecasting

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Track 25: Digital Epidemiology and AI-Based Disease Forecasting

This track explores the use of digital data, artificial intelligence, and advanced analytics in epidemiology to predict, monitor, and respond to disease trends. It emphasizes real-time surveillance, predictive modeling, and data-driven public health decision-making.

Key Focus Areas
  • Digital epidemiology and real-time surveillance
  • AI-based disease prediction and forecasting
  • Big data analytics for public health
  • Early warning systems and outbreak detection
  • Data integration and health intelligence


Importance
Digital epidemiology and AI-driven forecasting enable faster detection of health threats, improve preparedness, and support proactive public health responses.

Conclusion
Integrating digital epidemiology with AI-based forecasting strengthens public health intelligence and enhances global disease prevention and response capabilities.

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