Artificial intelligence and infectious diseases: an evidence-driven conceptual framework for research, public health, and clinical practice - 17/09/25

Doi : 10.1016/S1473-3099(25)00412-8

Anna Odone, ProfMD PhD ^a,^b,^{^{†
Contributed equally},}⁎ , Chiara Barbati, MD ^a,^{^{†
Contributed equally}}, Silvia Amadasi, MD ^c,^d, Tanja Schultz, ProfPhD ^e, David B Resnik, PhD ^f
^a School of Public Health, Department of Public Health, Experimental, and Forensic Medicine, University of Pavia, Pavia, Italy
^b Medical Direction, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
^c National PhD Programme in One Health approaches to infectious diseases and life science research, Department of Public Health, Experimental and Forensic Medicine, University of Pavia, Pavia, Italy
^d Department of Infectious and Tropical Diseases, ASST Spedali Civili Di Brescia, Brescia, Italy
^e Cognitive Systems Lab, Faculty 3 - Mathematics and Computer Science, University of Bremen, Bremen, Germany
^f National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA

^*Correspondence to: Prof Anna Odone, School of Public Health, Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, ItalySchool of Public HealthDepartment of Public HealthExperimental and Forensic MedicineUniversity of PaviaPavia27100Italy

Sous presse. Épreuves corrigées par l'auteur. Disponible en ligne depuis le Wednesday 17 September 2025

Summary

As artificial intelligence (AI) is projected to radically shape health care, its role in infectious disease prevention and management is drawing attention. AI offers promising opportunities to help tackle infectious disease threats and improve clinical management, outbreak detection, and infection control. As part of a dedicated Series on AI and infectious diseases, this paper sets the scene by proposing a conceptual framework that, building upon available AI models and data sources related to pathogens, human hosts, and the environment, comprehensively identifies selected domains where AI can be applied across infectious disease research, public health, and clinical practice. Building on this foundation, the two companion papers in the Series follow with an in-depth exploration of AI applications in diagnostics and antimicrobial resistance. We provide an overview of current and future applications of AI in infectious disease prevention and management, exploring the broad potential, available experimental evidence, real-life implementation examples, and technical normative, ethical, and policy barriers.

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