Sanders Pim, Vanderhaeghen Wannes, Fertner Mette, Fuchs Klemens, Obritzhauser Walter, Agunos Agnes, Carson Carolee, Borck Høg Birgitte, Dalhoff Andersen Vibe, Chauvin Claire, Hémonic Anne, Käsbohrer Annemarie, Merle Roswitha, Alborali Giovanni L, Scali Federico, Stärk Katharina D C, Muentener Cedric, van Geijlswijk Ingeborg, Broadfoot Fraser, Pokludová Lucie, Firth Clair L, Carmo Luís P, Manzanilla Edgar Garcia, Jensen Laura, Sjölund Marie, Pinto Ferreira Jorge, Brown Stacey, Heederik Dick, Dewulf Jeroen
The Netherlands Veterinary Medicines Institute (SDa), Utrecht, Netherlands.
Centre of Expertise on Antimicrobial Consumption and Resistance in Animals (AMCRA), Brussels, Belgium.
Front Vet Sci. 2020 Aug 21;7:540. doi: 10.3389/fvets.2020.00540. eCollection 2020.
The acknowledgment of antimicrobial resistance (AMR) as a major health challenge in humans, animals and plants, has led to increased efforts to reduce antimicrobial use (AMU). To better understand factors influencing AMR and implement and evaluate stewardship measures for reducing AMU, it is important to have sufficiently detailed information on the quantity of AMU, preferably at the level of the user (farmer, veterinarian) and/or prescriber or provider (veterinarian, feed mill). Recently, several countries have established or are developing systems for monitoring AMU in animals. The aim of this publication is to provide an overview of known systems for monitoring AMU at farm-level, with a descriptive analysis of their key components and processes. As of March 2020, 38 active farm-level AMU monitoring systems from 16 countries were identified. These systems differ in many ways, including which data are collected, the type of analyses conducted and their respective output. At the same time, they share key components (data collection, analysis, benchmarking, and reporting), resulting in similar challenges to be faced with similar decisions to be made. Suggestions are provided with respect to the different components and important aspects of various data types and methods are discussed. This overview should provide support for establishing or working with such a system and could lead to a better implementation of stewardship actions and a more uniform communication about and understanding of AMU data at farm-level. Harmonization of methods and processes could lead to an improved comparability of outcomes and less confusion when interpreting results across systems. However, it is important to note that the development of systems also depends on specific local needs, resources and aims.
抗菌药物耐药性（AMR）被公认为人类、动物和植物面临的一项重大健康挑战，这促使人们加大了减少抗菌药物使用（AMU）的力度。为了更好地了解影响AMR的因素，并实施和评估减少AMU的管理措施，掌握关于AMU数量的足够详细信息非常重要，最好是用户（农民、兽医）和/或开处方者或提供者（兽医、饲料厂）层面的信息。最近，一些国家已经建立或正在开发动物AMU监测系统。本出版物的目的是概述已知的农场层面AMU监测系统，并对其关键组成部分和流程进行描述性分析。截至2020年3月，已确定来自16个国家的38个活跃的农场层面AMU监测系统。这些系统在许多方面存在差异，包括收集哪些数据、进行何种类型的分析及其各自的输出。同时，它们共享关键组成部分（数据收集、分析、基准比较和报告），导致面临类似的挑战，需要做出类似的决策。针对不同组成部分提供了建议，并讨论了各种数据类型和方法的重要方面。本概述应为建立或使用此类系统提供支持，并可能有助于更好地实施管理行动，以及在农场层面就AMU数据进行更统一的沟通和理解。方法和流程的协调一致可能会提高结果的可比性，并在跨系统解释结果时减少混淆。然而，需要注意的是，系统的开发也取决于特定的当地需求、资源和目标。
