Transforming one health antimicrobial resistance surveillance in resource-limited countries (RLCs): From point-of-care diagnostics to AI-driven decision support.

Abstract

Antimicrobial resistance (AMR) is an emerging global problem, particularly for, resource-limited countries (RLCs) with limited capacity to diagnose diseases, inadequate surveillance systems, insufficient antimicrobial stewardship, and poor, health facilities. Conventional AMR surveillance relies primarily on post hoc laboratory, reporting and is not able to provide real-time data to aid in making effective clinical and, public health decisions. AMR surveillance is being revolutionized with the introduction, of point-of-care (PoC) diagnostics, digital health technologies, and artificial intelligence, (AI) that offer rapid pathogen identification, real-time data collection, and predictive, analysis. This review highlights the evolution of the AMR surveillance system from, conventional lab-based techniques to using AI and data to inform decision-making for, RLCs. Evidence is being collected on new PoC diagnostic platforms, biosensors, genomic surveillance, and Internet of Things (IoT) technologies and machine learning, (ML) algorithms developed from clinical, microbiological, genomic, and epidemiological, data to help improve resistance detection, antimicrobial prescribing, antimicrobial, stewardship, and outbreak prediction. We also explore the challenges of, implementation, such as lack of digital infrastructure, data interoperability, workforce, capacity, algorithmic bias, ethical and regulatory considerations, and sustainable, funding in AMR surveillance. The potential of new innovations like Mobile health, (mHealth), Internet of Things (IoT), Federated Learning (FL), and AI is highlighted as, necessary tools to help ensure greater scale, transparency, and equitable deployment., Lastly, we suggest an integrated approach, which brings together AMR PoC, diagnostics, clinical decision support using AI, and One Health surveillance to improve, the monitoring and response to AMR. Therefore, this review provides a pathway to, implementing resilient, intelligent, and equitable AMR surveillance systems and, illustrates how technological innovation can be linked to AMR system implementation, for better patient outcomes and implementation of evidence-based public health, policies in RLCs.