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Abstract Globally, the livestock sector plays a crucial role in ensuring food security and nutrition while supporting livelihoods of millions. However, antimicrobial resistance (AMR) poses a serious threat to the availability, accessibility, and safety of livestock-derived products. AMR has significant impacts on society in the form of increased mortality, rising healthcare costs, loss in Gross Domestic Product, and driving large populations into poverty by Rendering Many treatment options ineffective. The impact of AMR is projected to rise globally, with over ten million related deaths predicted annually by 2050—equivalent to the current global annual death toll from cancer. The challenge with AMR is its rapid evolution, outpacing our capacity to manage it. Livestock farming systems are a major source of AMR transmission, driven by the rising global demand for protein alongside stagnation in cereal production. In this review, we provide a concise overview of the development of AMR in livestock, the modes of transmission, mechanisms of antimicrobial resistance gene transfer, along with One Health approaches and other control strategies. Furthermore, we highlight the use of artificial intelligence algorithms to process extensive data from diverse sources, utilize historical data to forecast potential AMR outbreaks, swiftly examine bacterial genomes to detect AMR genes, and predict dissemination, providing a basis for choosing the optimal antibiotics for individual patients based on unique infection and resistance profiles.
Panicker et al. (Thu,) studied this question.