Genomic determinants of antimicrobial resistance in surveillance systems: from detection to decision-relevant interpretation for clinical and public health action

Genomic surveillance has become central to controlling antimicrobial resistance (AMR), yet a persistent gap remains between genomic data generation and its translation into clinical or public health action. This review, drawing on a structured search of PubMed, Embase, Scopus, and Web of Science (2014–2025), critically examines how genomic resistance determinants are interpreted within surveillance frameworks, distinguishing detection, prediction, and decision relevance. Key interpretive challenges involve gene expression variability, genomic context, horizontal gene transfer, and fitness trade-offs. Comparative analysis of bioinformatics tools including AMRFinderPlus, ResFinder, PointFinder, Pathogenwatch, and Kleborate reveals substantial inter-tool variability that directly affects predictive validity, while multi-omics evidence demonstrates that transcriptomic and proteomic integration enhances accuracy beyond gene detection alone. The review proposes a decision-oriented framework linking molecular evidence to therapeutic guidance, outbreak control, and policy design, identifying three research priorities: standardisation of genotype-phenotype validation models, development of integrated multi-omics surveillance pipelines, and harmonisation of decision thresholds across international networks.