Coordinating AMR Reporting with the Agri-Food Canada Database

Challenge

Antimicrobial resistance (AMR) is an emerging and significant issue impacting livestock production and food supply chains. Addressing this challenge requires a multifaceted approach, including policy interventions aimed at promoting more responsible antimicrobial use among stakeholders in the livestock industry, such as producers and veterinarians. However, current systems for tracking AMR are fragmented, with multiple reporting agencies using inconsistent data collection methods. This lack of standardization makes it difficult to quantify the risks associated with AMR and assess the effectiveness of existing policies. Data is crucial in combating AMR, as it enables decision-makers and researchers to identify trends and draw connections between factors influencing AMR and the responsible use of antimicrobials.

Research

To address AMR tracking challenges, Dr. Nicole Ricker’s team is working to unify and streamline AMR surveillance data across Canada as part of the Agri-Food Data Canada (ADC) platform. Built around the FAIR principles (Findable, Accessible, Interoperable, and Reusable), the platform will provide data management schemas to help standardize sampling, analysis and reporting of AMR surveillance data to ensure data harmonization and promote data sharing. Together with colleagues at McMaster University and Simon Fraser University, Dr. Ricker is also developing a mobile element ontology (MOBIO) to facilitate accurate annotation of the genes involved in transferring resistance between different bacteria. The project’s key objectives include: 1) Supporting ADC growth by incorporating gene ontology dictionaries and standardizing AMR data; 2) Developing data analysis pipelines that protect client confidentiality while promoting data harmonization practices; and 3) Creating training materials to facilitate data sharing between institutions. As part of this ongoing project, Ricker’s team is also developing training materials on data generation and collection, as well as creating frameworks for data analysis across the newly integrated systems.

Results

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Impact

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