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Book (stand-alone)Technical reportJoint FAO/WHO/OIE Expert Meeting on Critically Important Antimicrobials
Report of the FAO/WHO/OIE Expert Meeting FAO Headquarters, Rome 26-30 November 2007
2008The need for access to antimicrobials in both human and veterinary medicine is critical. However, with increasing resistance to antimicrobials, it has been necessary for WHO and OIE to develop lists of critically important antimicrobials for human and veterinary use respectively. A comparison of these two lists highlights the overlap that occurs. Therefore FAO/WHO/OIE implemented an expert meeting to review the overlap, identify the current and potential hazards to public health result ing from this and, find an appropriate balance between animal health needs and public health considerations. In addition this meeting sought to identify the combinations – human-pathogen-antimicrobial use and animal species – that could be considered by risk managers as the priority combinations for future risk-benefit assessment and review current management strategies and options for maintaining the efficacy of critically important antimicrobials for humans and animals. This report contains the findings of that expert meeting and gives particular attention to principles and approaches for prioritization for risk assessment and the identification and characterization of preliminary risk management activities for minimizing the risk of antimicrobial resistance associated with food animals. In addition it includes a series of recommendations to FAO, WHO, OIE and national governments related to assessment and management of antimicrobial resistance resulting from the use of antimicrobials in food animals. -
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Book (stand-alone)Technical bookDigital agriculture in action
ArtificiaI intelligence for agriculture
2021Also available in:
No results found.This publication on artificial intelligence (AI) for agriculture is the fifth in the E-agriculture in Action series, launched in 2016 and jointly produced by FAO and ITU. It aims to raise awareness about existing AI applications in agriculture and to inspire stakeholders to develop and replicate the new ones. Improvement of capacity and tools for capturing and processing data and substantial advances in the field of machine learning open new horizons for data-driven solutions that can support decision-making, facilitate supervision and monitoring, improve the timeliness and effectiveness of safety measures (e.g. use of pesticides), and support automation of many resource-consuming tasks in agriculture. This publication presents the reader with a collection of informative applications highlighting various ways AI is used in agriculture and offering valuable insights on the implementation process, success factors, and lessons learnt.