Abdul Ghafur, Miki Nagao, Souha S. Kanj, Salam Abbara, Pierre Tattevin, Mariette Awad, Maya Dagher, Linus K. Ndegwa, Gathai Mundia, Jeroen Schouten, Huong T.L. Vu, Gabriel Levy Hara, Maneesh Paul Satyaseela, Mamoon A. Aldeyab, Raksha K. Bhat, Nitin Bansal, Heiman F.L. Wertheim
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引用次数: 0
Abstract
Background
Antimicrobial resistance continues to threaten the effectiveness of modern medicine and poses major public health challenges worldwide. Antimicrobial stewardship (AMS) programmes are essential to mitigate inappropriate antimicrobial use but are often resource-intensive and difficult to sustain. Advances in artificial intelligence (AI) have generated interest in its potential to support stewardship activities across clinical, operational, and public health domains.
Objectives
To critically review the current and emerging roles of AI in AMS and to examine its opportunities, limitations, and implications for clinical practice, public health, and health systems globally.
Methods
We conducted a narrative review of the literature on AI applications relevant to AMS, including diagnostic support, antimicrobial prescribing, behavioural and implementation science, infection prevention, surveillance, One Health approaches, drug discovery, and governance. Particular attention was paid to ethical considerations, human oversight, and applicability in low- and middle-income country settings.
Results
AI has demonstrated potential to enhance diagnostic precision, support clinical decision-making, optimise antimicrobial use, strengthen surveillance systems, and inform targeted stewardship interventions. However, challenges related to data quality, bias, interpretability, workflow integration, ethical governance, and equity remain significant. AI systems developed in high-income settings may not be directly transferable to low- and middle-income countries without careful adaptation and local validation.
Conclusions
AI should be viewed as a decision-support tool that augments, rather than replaces, AMS expertise. When implemented responsibly within robust governance frameworks and aligned with AMS principles, AI can contribute meaningfully to improved antimicrobial use and antimicrobial resistance control. Sustained human leadership, equity-focused deployment, and health system strengthening remain essential.
期刊介绍:
The Journal of Global Antimicrobial Resistance (JGAR) is a quarterly online journal run by an international Editorial Board that focuses on the global spread of antibiotic-resistant microbes.
JGAR is a dedicated journal for all professionals working in research, health care, the environment and animal infection control, aiming to track the resistance threat worldwide and provides a single voice devoted to antimicrobial resistance (AMR).
Featuring peer-reviewed and up to date research articles, reviews, short notes and hot topics JGAR covers the key topics related to antibacterial, antiviral, antifungal and antiparasitic resistance.