ARTIFICIAL INTELLIGENCE IN EPIDEMIOLOGY

Introduction: Epidemiology studies the distribution and determinants of health events in populations to control and prevent diseases. The integration of artificial intelligence (AI) has recently transformed epidemiology by enabling analysis of complex, large-scale data to improve disease surveillance, prediction, and decision-making. Aim: To summarize recent advances in AI applications within epidemiology. Materials and Methods: A structured search of major databases identified English-language studies from 2018 to 2025. Relevant articles on AI techniques for modeling, prediction, outbreak detection, and integration with traditional methods were included. \ Results and Discussion: AI’s role in epidemiology has evolved from early machine learning to advanced deep learning and natural language processing, enhancing outbreak tracking, disease modeling, geospatial visualization, diagnosis, and public sentiment analysis. Integration of AI with mechanistic models has improved forecasting and intervention assessments by capturing complex transmission dynamics and adapting to real-time data. AI-driven tools outperform traditional methods in predictive accuracy, enabling earlier detection of diseases. AI also processes large, heterogeneous datasets, uncovering non-linear relationships and supporting causal inference. Challenges remain, including data bias, privacy concerns, and the opacity of “black box” models. Addressing these requires ethical frameworks, transparency, and interdisciplinary collaboration. The expanding AI epidemiology market, driven by globalization, climate change, and big data, offers opportunities for improved public health responsiveness. Future research should focus on standardizing validation, integrating biological and social factors, and ensuring transparency. Conclusion: AI has transformative potential for epidemiology, but responsible use depends on overcoming ethical, technical, and structural challenges through collaborative governance to promote health equity and public trust.