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Introduction: As part of the EU Joint Action on Antimicrobial Resistance (AMR) and Healthcare-Associated Infections, an initiative has been launched to build the European AMR Surveillance network in veterinary medicine (EARS-Vet). So far, activities included mapping national systems for AMR surveillance in animal bacterial pathogens, and defining the EARS-Vet objectives, scope, and standards. Drawing on these milestones, this study aimed to pilot test EARS-Vet surveillance, namely to (i) assess available data, (ii) perform cross-country analyses, and (iii) identify potential challenges and develop recommendations to improve future data collection and analysis. Methods: Eleven partners from nine EU/EEA countries participated and shared available data for the period 2016-2020, representing a total of 140,110 bacterial isolates and 1,302,389 entries (isolate-antibiotic agent combinations). Results: Collected data were highly diverse and fragmented. Using a standardized approach and interpretation with epidemiological cut-offs, we were able to jointly analyze AMR trends of 53 combinations of animal host-bacteria-antibiotic categories of interest to EARS-Vet. This work demonstrated substantial variations of resistance levels, both among and within countries (e.g., between animal host species). Discussion: Key issues at this stage include the lack of harmonization of antimicrobial susceptibility testing methods used in European surveillance systems and veterinary diagnostic laboratories, the absence of interpretation criteria for many bacteria-antibiotic combinations of interest, and the lack of data from a lot of EU/EEA countries where little or even surveillance currently exists. Still, this pilot study provides a proof-of-concept of what EARS-Vet can achieve. Results form an important basis to shape future systematic data collection and analysis. [ABSTRACT FROM AUTHOR]

IntroductionAs part of the EU Joint Action on Antimicrobial Resistance (AMR) and Healthcare-Associated Infections, an initiative has been launched to build the European AMR Surveillance network in veterinary medicine (EARS-Vet). So far, activities included mapping national systems for AMR surveillance in animal bacterial pathogens, and defining the EARS-Vet objectives, scope, and standards. Drawing on these milestones, this study aimed to pilot test EARS-Vet surveillance, namely to (i) assess available data, (ii) perform cross-country analyses, and (iii) identify potential challenges and develop recommendations to improve future data collection and analysis.MethodsEleven partners from nine EU/EEA countries participated and shared available data for the period 2016–2020, representing a total of 140,110 bacterial isolates and 1,302,389 entries (isolate-antibiotic agent combinations).ResultsCollected data were highly diverse and fragmented. Using a standardized approach and interpretation with epidemiological cut-offs, we were able to jointly analyze AMR trends of 53 combinations of animal host-bacteria–antibiotic categories of interest to EARS-Vet. This work demonstrated substantial variations of resistance levels, both among and within countries (e.g., between animal host species).DiscussionKey issues at this stage include the lack of harmonization of antimicrobial susceptibility testing methods used in European surveillance systems and veterinary diagnostic laboratories, the absence of interpretation criteria for many bacteria–antibiotic combinations of interest, and the lack of data from a lot of EU/EEA countries where little or even surveillance currently exists. Still, this pilot study provides a proof-of-concept of what EARS-Vet can achieve. Results form an important basis to shape future systematic data collection and analysis.

Tackling antimicrobial resistance (AMR) is a goal for many countries. Integrated surveillance of antimicrobial use (AMU) and resistance is a prerequisite for effective risk mitigation. Regular evaluation of any surveillance is needed to ensure its effectiveness and efficiency. The question is how to evaluate specifically integrated surveillance for AMU and AMR. In an international network called CoEvalAMR, we have developed guidelines for selection of the most appropriate tools for such an evaluation. Moreover, we have assessed different evaluation tools as examples using a country case format and a methodology with a focus on the user's experience. This paper describes the updated methodology, which consists of a brief introduction to the case and to the tool separately. Moreover, there are 12 functional aspects and nine content themes which should be scored using a 4-tiered scale. Additionally, four Strengths, Weaknesses, Opportunities, Threats (SWOT) questions should be addressed. Results are illustrated using radar diagrams. An example of application of the updated methodology is given using the ECoSur evaluation tool. No tool can cover all evaluation aspects comprehensively in a user-friendly manner, so the choice of tool must be based upon the specific evaluation purpose. Moreover, adequate resources, time and training are needed to obtain useful outputs from the evaluation. Our updated methodology can be used by tool users to share their experience with available tools, and hereby assist other users in identifying the most suited tool for their evaluation purpose. Additionally, tool developers can get valuable information for further improvements of their tool.

Abstract Antimicrobial resistance (AMR) resulting from antimicrobial use (AMU) is an emerging threat to global health. One of the key elements for a better understanding and management of AMU and AMR is to develop effective and efficient integrated surveillance systems that consider the complex epidemiology of these issues and the impacts of resistance on humans, animals and the environment. Consequently, for this project, an international consortium of experts from multiple fields called CoEvalAMR was formed with the objectives to study user needs, characterise and compare existing tools for the evaluation of integrated AMU and AMR surveillance, apply them to case studies, and elaborate guidance on the purpose-fit selection and the use of the tools. For the comparison of evaluation tools, questions were extracted from existing tools and attributed to themes, to assess the user needs, interviews were conducted with national key stakeholders, and we applied a series of different evaluation tools to understand and document their strengths and weaknesses. The guidance was refined iteratively. From 12 evaluation tools, 1117 questions/indicators were extracted and attributed to seven emerging themes. Twenty-three experts were interviewed, who suggested to increase the ease-of-use, grant open access, provide web-based interfaces and allow results to be automatically generated. Respondents also wished for tools providing the flexibility to conduct a rapid review, or an in-depth analysis of the surveillance system, depending on the evaluation objectives. The case studies emphasised that proper evaluations require adequate resources, typically requiring the involvement of several assessors and/or stakeholders, and can take weeks or months to complete. The resulting web-based guidance comprises six main sections: 1. Introduction to surveillance evaluation, 2. Evaluation of surveillance for AMU and AMR, 3. Evaluation tools, 4. Support for selecting an evaluation tool, 5. Case studies and 6. Directory of existing tools. The audience for the guidance is personnel working in public, private, and non-governmental organisations, from public health, animal health, plant health and environmental health, at local, national and international levels. We conclude that the field is challenged by opposing user needs for reduction and simplicity versus system approaches allowing the synthesis of that knowledge to sufficiently reflect the complexity of AMU and AMR ecology for real-world decisions. The CoEvalAMR web platform allows a better understanding of the different evaluation tools and assists users in the selection of an approach that corresponds to their evaluation needs. The CoEvalAMR consortium continues to address remaining gaps and consolidate evaluation tools and approaches in the future. One Health Impact Statement Antimicrobial resistance (AMR) resulting from antimicrobial use is a threat to human and animal health and may have unknown impacts on the environment. To understand how governance and human behaviour relate to AMR, it is important to implement integrated surveillance across the human, animal and environmental sectors. In this work, we describe the development of guidance on how to evaluate such surveillance, what the available tools cover and what gaps remain. The integration of surveillance is essential to address the interrelated pathways across the system. Consequently, the work with the reporting interdisciplinary consortium revealed that the broad diversity of users and their needs imply that a sustained exchange is needed to address the evolving challenge. This will be important to develop meaningful measures of impact and to avoid fixing one sector’s problems at the expense of another.

Integrated surveillance systems for antimicrobial use (AMU) and antimicrobial resistance (AMR) require regular evaluation to ensure the effectiveness and efficiency of the system. An important step in the evaluation is to choose an appropriate tool for the purpose of the evaluation. The “Integrated Surveillance System Evaluation” (ISSE) framework is a conceptual framework that was developed to evaluate One Health (OH) integration in surveillance system for AMU/AMR. This study aimed to evaluate the performance and value of integrated surveillance system for AMU/AMR in England by applying the ISSE framework, which was used to develop data collection protocols and define the study design. A qualitative study using semi-structured interviews was conducted to collect the data and analyse it thematically. Eighteen stakeholders from human, animal, food and environment sectors that are involved in AMU/AMR surveillance were interviewed. Four main themes emerged from the analysis: (1) Cross-sectoral integration in the surveillance system for AMU/AMR; (2) Production of OH outputs and outcomes; (3) Drivers and barriers to cross-sectoral collaboration; and 4) Need for more cross-sectoral collaboration. The findings showed that there were links between integrated surveillance information, decision making and interventions. However, there were only few OH examples, such as the UK AMR contingency plan, where the potential of cross-sectoral collaboration was fully exploited. A lot of the benefits described were related to the generation of information and increase in knowledge and understanding without links to how the information generated was used. While these intangible benefits have a value on their own, being able to link surveillance information and mitigation measures would help to enhance the value of integrated surveillance. In terms of improvement, the main areas identified were the development of more harmonised methods for data collection and analysis, provision of resources dedicated to cross-sectoral collaboration, improved coordination, and collection of surveillance data from the environment and from companion animals. By identifying links between OH surveillance information produced and various outputs and outcomes; this study helped to understand the wider benefits of integrated surveillance for AMU/AMR in England and provided insights on how the system could be improved and efficiency increased.

Quantification and tracking of antimicrobial use (AMU) are key factors for the development of responsible antimicrobial stewardship programs and comparison between countries. Global finfish aquaculture growth and increased AMU creates the potential for exchange of antimicrobial resistance between aquatic and terrestrial environments, making AMU surveillance imperative for this industry. The objective of this review is to collate current literature on AMU surveillance indicators and their application to commercial finfish aquaculture production. A systematic search strategy was applied to five databases: Medline, Embase, Agricola, CAB abstracts, and Biosis. To be included, studies must report on at least one AMU surveillance indicator for use in animals. There is no single, standardized indicator suitable to report finfish aquaculture AMU. The type and availability of finfish aquaculture data presents unique considerations for AMU reporting. Ultimately, the indicator used should be fit-for-purpose to satisfy the objective of the surveillance program, motivation for comparison and provide useful information to the industry stakeholders. Finfish aquaculture total annual slaughter weight allows estimation of biomass for the population correction unit (PCU) to report annual total mg of active antimicrobial ingredient per PCU. These data are commonly reported by finfish aquaculture-producing countries, allowing for international comparisons. However, this precludes the ability to compare to terrestrial livestock where the PCU is based on animal numbers and an average treatment weight, which are not available for finfish aquaculture. The mg per adjusted PCU indicator provides an interesting alternative that incorporates the length of the marine grow-out phase for finfish, but is subject to the same limitations. The number of defined daily doses animal per animal-days-at-risk is useful but also limited by a lack of a defined average treatment weight. The concept of average treatment weight remains challenging for the industry as it does not accurately reflect the timing of actual AMU to fish in the system. The term “average biomass” is more reflective of the intent of AMU surveillance indicators. Defining an average treatment weight, or average biomass, will require industry engagement, which is crucial if AMU reporting is to be deemed credible and provide value back to the finfish aquaculture industry.

Antimicrobial resistance (AMR) is a global health problem. Bacteria carrying resistance genes can be transmitted between humans, animals and the environment. There are concerns that the widespread use of antimicrobials in the food chain constitutes an important source of AMR in humans, but the extent of this transmission is not well understood. The aim of this review is to examine published evidence on the links between antimicrobial use (AMU) in the food chain and AMR in people and animals. The evidence showed a link between AMU in animals and the occurrence of resistance in these animals. However, evidence of the benefits of a reduction in AMU in animals on the prevalence of resistant bacteria in humans is scarce. The presence of resistant bacteria is documented in the human food supply chain, which presents a potential exposure route and risk to public health. Microbial genome sequencing has enabled the establishment of some links between the presence of resistant bacteria in humans and animals but, for some antimicrobials, no link could be established. Research and monitoring of AMU and AMR in an integrated manner is essential for a better understanding of the biology and the dynamics of antimicrobial resistance.

The article discusses a study which described the main strengths and weaknesses of the French surveillance system for Salmonella based on a national system for human cases and animal reservoirs. Different approaches were compared using grid analysis. The study showed that passive systems are useful for detecting emerging or unusual events and for early warning of outbreaks, and for producing time series of cases. It is stated that active surveillance data are key elements in the application of risk analysis.

Antimicrobial resistance (AMR) is a global health problem. Bacteria carrying resistance genes can be transmitted between humans, animals and the environment. There are concerns that the widespread use of antimicrobials in the food chain constitutes an important source of AMR in humans, but the extent of this transmission is not well understood. The aim of this review is to examine published evidence on the links between antimicrobial use (AMU) in the food chain and AMR in people and animals. The evidence showed a link between AMU in animals and the occurrence of resistance in these animals. However, evidence of the benefits of a reduction in AMU in animals on the prevalence of resistant bacteria in humans is scarce. The presence of resistant bacteria is documented in the human food supply chain, which presents a potential exposure route and risk to public health. Microbial genome sequencing has enabled the establishment of some links between the presence of resistant bacteria in humans and animals but, for some antimicrobials, no link could be established. Research and monitoring of AMU and AMR in an integrated manner is essential for a better understanding of the biology and the dynamics of antimicrobial resistance. [ABSTRACT FROM AUTHOR]