AI in Epidemiology
Iris-Panagiota Efthymiou · 2025
This chapter explores the role of artificial intelligence in epidemiology, focusing on its application in early outbreak detection and disease spread prediction. It examines how machine learning, natural language processing, and predictive analytics are applied to real-time data from clinical, environmental, and digital sources. The chapter demonstrates the integration of AI into public health surveillance systems and discusses the ethical, technical, and infrastructural challenges involved. It highlights the potential of AI to process large, heterogeneous datasets at speed and scale, enabling earlier intervention and resource allocation during emerging health crises. By analyzing historical trends and identifying hidden patterns, AI models offer critical support to decision-makers in managing uncertainty and enhancing response strategies. This chapter argues for an interdisciplinary and transparent approach to algorithm design, data governance, and stakeholder collaboration.