Antimicrobial resistance (AMR) poses an escalating threat to human health, food systems, and environmental stability worldwide. This review paper evaluates the One Health paradigm as a comprehensive, interdisciplinary strategy to mitigate antibiotic resistance by tackling its interconnected factors within clinical, veterinary, and ecological spheres. It analyses the effects of antibiotic misuse, zoonotic transmission, and environmental reservoirs on the escalation of resistance, while evaluating the systemic barriers that hinder coordinated surveillance, policy alignment, and equitable resource distribution, particularly in low- and middle-income countries. Innovative techniques like as CRISPR, metagenomics, and artificial intelligence (AI) are examined for their capacity to transform the detection, prediction, and intervention of antimicrobial resistance (AMR). AI-driven surveillance systems offer exceptional capabilities in real-time monitoring and data integration across several domains. Case studies from Denmark’s veterinary stewardship reforms and advanced wastewater monitoring underscore the effectiveness of targeted initiatives supported by robust governance. Despite these achievements, significant difficulties remain, such as infrastructure inadequacies, regulatory fragmentation, and opposition to change among stakeholders. This evaluation highlights that effective AMR containment requires not only technological breakthroughs but also coordinated policies, public engagement, and sustained worldwide collaboration. The comprehensive implementation of the One Health idea offers a scalable and equitable framework to preserve antibiotic efficacy and protect planetary health.
Jangid et al. (Fri,) studied this question.