Artificial intelligence and infectious diseases: an evidence-driven conceptual framework for research, public health, and clinical practice.

Abstract

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.