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

人们经常建议，预防抗生素耐药性（AMR）发展和传播的干预措施应针对畜牧业。为了人类（和动物）的长期健康利益，农业的潜在成本往往被认为是“值得的”。通过合作伙伴之间的共同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，考虑到人类健康、AMU和AMR的不同情景，在国家一级，什么样的农场级抗菌药物使用（AMU）干预措施最有效？我们将使用统计、数学和经济模型来构建一个分区模型，该模型可以评估（i）动物、环境和人类传播抗生素耐药性之间的相互作用，以及（ii）“一个健康”的成本和收益之间的相互作用。我们将分析先前实施的干预措施的影响，为不同AMR情景下的未来干预措施建模提供信息。设置，成本和效益将通过专家启发通过一个由知识产权持有人主导的“知识中心”明确定义。这项工作不仅将提供明确的影响估计和一系列农场级AMU干预措施的排名，它还将提供对不确定性的洞察，突出未来的研究可能是最有价值的了解AMR干预效率从一个健康的角度。

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.