ArticlePathogens (Basel, Switzerland)2021
Informing Stewardship Measures in Canadian Food Animal Species through Integrated Reporting of Antimicrobial Use and Antimicrobial Resistance Surveillance Data-Part I, Methodology Development.
Article in Pathogens (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Antimicrobial use and Escherichia coli resistance patterns in Hungarian pig farms: a data-driven farm-level analysis.Scientific reports · 2026Article
- Integrated surveillance systems for antibiotic resistance in a One Health context: a scoping review.BMC public health · 2024Article
- Antimicrobial resistance in genericThe Canadian veterinary journal = La revue veterinaire canadienne · 2024Article
- Antimicrobial resistance in Enterococcus isolated from western Canadian cow-calf herds.BMC veterinary research · 2024Article
- Assessing antimicrobial resistance inEpidemiology and infection · 2023Article
- Article
- Canadian Collaboration to Identify a Minimum Dataset for Antimicrobial Use Surveillance for Policy and Intervention Development across Food Animal Sectors.Antibiotics (Basel, Switzerland) · 2022Article
- Associations between antimicrobial resistance in fecalFrontiers in microbiology · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study explores methodologies for the data integration of antimicrobial use (AMU) and antimicrobial resistance (AMR) results within and across three food animal species, surveyed at the farm-level by the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS). The approach builds upon existing CIPARS methodology and principles from other AMU and AMR surveillance systems. Species level data integration involved: (1) standard CIPARS descriptive and temporal analysis of AMU/AMR, (2) synthesis of results, (3) selection of AMU and AMR outcomes for integration, (4) selection of candidate AMU indicators to enable comparisons of AMU levels between species and simultaneous assessment of AMU and AMR trends, (5) exploration of analytic options for studying associations between AMU and AMR, and (6) interpretation and visualization. The multi-species integration was also completed using the above approach. In addition, summarized reporting of internationally-recognized indicators of AMR (i.e., AMR adjusted for animal biomass) and AMU (mg/population correction unit, mg/kg animal biomass) is explored. It is envisaged that this approach for species and multi-species AMU-AMR data integration will be applied to the annual CIPARS farm-level data and progressively developed over time to inform AMU-AMR integrated surveillance best practices for further enhancement of AMU stewardship actions.
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