Harnessing artificial intelligence for enhanced public health surveillance: a narrative review - Mendes, Vanessa I. S.; Mendes, Beatriz M. F.; Moura, Rui Pedro; Lourenço, Inês M.; Oliveira, Mariana F. A.; Ng, Kim Lee; Pinto, Cátia S. (Frontiers in Public Health, 2025)
Artificial intelligence (AI) has a transformative potential to revolutionize public health by addressing critical challenges in disease prevention, outbreak detection, and countermeasures distribution. Traditional public health surveillance methods often face limitations, such as delays in reporting, under-detection of cases, and the overwhelming complexity of managing large datasets. In contrast, AI technologies enable real-time analysis, enhance scalability, and support more effective decision-making, especially during health crises. This review examines the profound impact of AI on key areas of public health, with a particular focus on communicable diseases. It explores how AI-driven technologies are transforming disease monitoring and surveillance, outbreak prevention, and disease modeling, improving the ability to detect and respond to emerging health threats. Furthermore, the role of internet and social media in managing disease outbreaks through AI-powered systems is also highlighted, showcasing how AI can harness information from diverse data sources to enhance public health interventions. The review also delves into the regulatory landscape, emphasizing the importance of robust standards and frameworks, such as those established by the EU, for ensuring the safe, ethical, and responsible implementation of AI in public health. By shedding light on AI’s potential to improve real-time decision-making and support health crisis management, this paper underscores its transformative role in shaping the future of public health surveillance and response.