Selecting Efficient Farm-level Antimicrobial Stewardship Interventions from a One Health perspective

经常有人建议，预防抗菌素耐药性(AMR)发展和传播的干预措施应以畜牧业为目标。农业的潜在成本经常被认为是“值得的”，因为它对人类(和动物)的长期健康有利。然而，对每个系统的相对收益和成本的量化是缺乏的。通过合作伙伴之间的共享学习和现有数据的二次利用，我们计划回答这样一个问题：在英格兰、丹麦和塞内加尔的人类健康、AMU和AMR的不同情况下，在国家层面上，什么农场级别的抗菌剂使用(AMU)干预措施最有效？将效率定义为在给定设定的预算和一系列预期结果的情况下，资源使用的优化。我们将使用统计学、数学和经济建模来构建一个分区模型，该模型可以评估(I)动物、环境和人类传播AMR之间的相互作用，以及(Ii)一个健康项目的成本和收益之间的相互作用。我们将分析以前实施的干预措施的影响，以便为不同AMR情景下的未来干预措施建模提供信息。环境、成本和收益将通过利益相关者主导的“知识中心”通过专家启发进行具体定义。这项工作不仅将为一系列农场级别的AMU干预措施提供明确的影响估计和排名，还将提供对不确定性的洞察，突出未来研究在从One Health的角度理解AMR干预效率方面最有价值的地方。

It is often suggested that interventions to prevent the development and transmission of antimicrobial resistance (AMR) should be targeted at the livestock sector. The potential costs to agriculture are often argued as "worth it" for the long-term human (and animal) health benefits. However, a quantification of the relative benefits and costs for each system is lacking.Through shared learning across partners and secondary use of existing data, we plan on answering the question 'What farm-level antimicrobial usage (AMU) interventions are most efficient at the national-level, given different scenarios of human health, AMU and AMR, for England, Denmark and Senegal?', defining efficiency as the optimisation of resource use, given a set budget and a set of desired outcomes.We will use statistical, mathematical and economic modelling to construct a compartmental model that can assess (i) the interplay between animal, environment and human transmission of AMR, and (ii) the interplay between costs and benefits across One Health. We will analyse the impact of previously implemented intervention to inform modelling of future interventions under different AMR scenarios. Settings, costs and benefits will be specifically defined via expert elicitation through a stakeholder-led 'knowledge hub'.This work will not only provide explicit impact estimates and ranking for a range of farm-level AMU interventions, it will also provide insight into uncertainty, highlighting where future research could be most valuable in understanding AMR intervention efficiency from a One Health perspective.