Background: Antimicrobial resistance (AMR) is among the most pressing One Health issues. While interventions and policies with various targets and goals have been implemented, evidence about factors underpinning success and failure of interventions in different sectors is lacking. The objective of this study is to identify characteristics of AMR interventions that increase their capacity to impact AMR. This study focuses on AMR interventions targeting E. coli. Methods: We used the AMR-Intervene framework to extract descriptions of the social and ecological systems of interventions to determine factors contributing to their success. Results: We identified 52 scientific publications referring to 42 unique E. coli AMR interventions. We mainly identified interventions implemented in high-income countries (36/42), at the national level (16/42), targeting primarily one sector of society (37/42) that was mainly the human sector (25/42). Interventions were primarily funded by governments (38/42). Most intervention targeted a low leverage point in the AMR system, (36/42), and aimed to change the epidemiology of AMR (14/42). Among all included publications, 55% (29/52) described at least one success factor or obstacle (29/52) and 19% (10/52) identified at least one success factor and one obstacle. Most reported success factors related to communication between the actors and stakeholders and the role of media, and stressed the importance of collaboration between disciplines and external partners. Described obstacles covered data quality, access to data and statistical analyses, and the validity of the results. Conclusions: Overall, we identified a lack of diversity regarding interventions. In addition, most published E. coli interventions were poorly described with limited evidence of the factors that contributed to the intervention success or failure. Design and reporting guidelines would help to improve reporting quality and provide a valuable tool for improving the science of AMR interventions.

Antimicrobial resistance (AMR) affects the environment, and animal and human health. Institutions worldwide have applied various measures, some of which have reduced antimicrobial use and AMR. However, little is known about factors influencing the success of AMR interventions. To address this gap, we engaged health professionals, designers, and implementers of AMR interventions in an exploratory study to learn about their experience and factors that challenged or facilitated interventions and the context in which interventions were implemented. Based on participant input, our thematic analysis identified behaviour; institutional governance and management; and sharing and enhancing information as key factors influencing success. Important sub-themes included: correct behaviour reinforcement, financial resources, training, assessment, and awareness of AMR. Overall, interventions were located in high-income countries, the human sector, and were publicly funded and implemented. In these contexts, behaviour patterns strongly influenced success, yet are often underrated or overlooked when designing AMR interventions. Improving our understanding of what contributes to successful interventions would allow for better designs of policies that are tailored to specific contexts. Exploratory approaches can provide encouraging results in complex challenges, as made evident in our study. Remaining challenges include more engagement in this type of study by professionals and characterisation of themes that influence intervention outcomes by context.

Background/Objectives: Antibiotic use (ABU) in cats and dogs is a potential public health issue due to its direct contribution to the emergence of antibiotic resistance. In Switzerland, data on animal antibiotic treatments has been collected since 2020 via the Information System for ABU in Veterinary Medicine. This study focuses on the first implementation of a national benchmarking tool for ABU in cats and dogs in veterinary practices. Methods: The benchmarking tool is based on a practice-level indicator derived from the number of therapy days (pATI). Practices are compared separately for small animal practices and mixed practices, and for each animal species. The pATI is calculated based on the number of therapy days and is normalized by the number of consultations per species and per year. Practices were classified into four ABU categories based on their pATI: very high, high, acceptable, and no ABU. Thresholds for these categories are set according to Swiss legislation, using the 75th and 95th percentiles of the pATI values of all comparable practices. Results: By 2025, benchmarks were implemented in 686 veterinary facilities; a total of 667 (97.2%) received a pATI classification for ABU in dogs and 670 (97.7%) for ABU in cats. The median pATI was higher for cats than for dogs across all practice types. Similarly, the 75th and 95th percentile thresholds were also almost always twice as high for cats as for dogs across all practice types. Conclusions: To our knowledge, this is the first time a benchmarking tool for ABU has been implemented at a national level for cats and dogs. The benchmarking tool is expected to drive long-term changes in ABU practices.