Application of Artificial Intelligence in Infectious Disease Surveillance in sub-Saharan Africa: A Scoping Review

Key Points

• This review explores how artificial intelligence can enhance infectious disease surveillance in sub-Saharan Africa.
• Conducted a scoping review of AI applications in infectious disease surveillance.
• Focused on machine learning techniques and their effectiveness.
• Evaluated the challenges such as data and skills gaps affecting AI adoption.
• Machine learning is the primary method used for AI surveillance.
• AI effectively predicts outbreaks and identifies disease hotspots, particularly for malaria and COVID-19.
• Ensemble models show better performance compared to single models in outbreak predictions.