Key points are not available for this paper at this time.
Antimicrobial resistance (AMR) and antibiotic resistance (ABR) represent one of the most pressing global health threats, driven by the complex interplay between human, animal, and environmental factors. The One Health resistome framework recognises that resistance genes circulate continuously across clinical, agricultural, and environmental compartments through horizontal gene transfer, co-selection mechanisms, and anthropogenic contamination. This comprehensive review synthesises current evidence on integrated AMR surveillance, examining how digital technologies are transforming our capacity to monitor, predict, and respond to resistance emergence. Key advances include whole-genome sequencing enabling high-resolution pathogen tracking, metagenomics revealing environmental resistome diversity, machine learning algorithms predicting resistance phenotypes with > 85% accuracy, and point-of-care diagnostics extending sophisticated testing to resource-limited settings. Geographic information systems facilitate spatial hotspot identification, while wastewater-based surveillance provides early warning capabilities, detecting resistance genes before clinical manifestation. Despite technological progress, substantial challenges persist: fragmented data streams across sectors, lack of standardised environmental monitoring methods, limited laboratory capacity in low- and middle-income countries, and chronic underfunding. Emerging technologies, portable nanopore sequencing, CRISPR-based diagnostics, artificial intelligence, and blockchain-enabled data governance promise to address these gaps. Realising comprehensive One Health resistome surveillance requires sustained investment in interoperable digital infrastructure, international standardisation, capacity building, and political commitment to cross-sectoral coordination, prioritising equitable global implementation.
Majumdar et al. (Tue,) studied this question.