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D-1.2. Description of the specified AMR prevalence/frequency and AMU at population/country/regional level. D-1.3. A list of the regions identified for in-depth analysis, and a report including the assessments of parallel trends and estimates of potential associations between AMR and AMU.

Mesa-Varona, O; Velasova, M; Boone, I; Tenhagen, B-A

Human and animal health improvement is the main target of the One Health approach 1. Antimicrobial resistance (AMR) is one of the main challenges at a global scale. Global and National Action Plans have been set up by many countries to try to tackle the AMR threat.

ARDIG is a One Health European Joint Programme (EJP) project which is carried out under the need to increase knowledge about AMR 2. The project aims to understand the dynamics of AMR by assessing national trends and farm/hospital trends from six different European countries (Spain, Norway, Germany, the Netherlands, France and the United Kingdom) with the final objective of developing strategies that help to reduce the spread of resistant bacteria at European level.

This report is focussed on defining and describing available consumption data from humans and livestock together with resistance data of E.coli from urinary samples in humans, livestock and meat. This report shows also first descriptive analyses addressing the task 1.2. of WP1 ARDIG: Investigation of trends, associations and risk factors. Further analyses are under way.

AMR data has been interpreted in this delivery by different standards and different evaluation criteria in order to facilitate the analysis of associations. These standards are the European Committee for Antimicrobial Susceptibility Testing (EUCAST) and the French Society of Microbiology (CASFM). EUCAST provides two evaluation criteria, Epidemiological Cut-offs (ECOFFs) and Clinical Break-Points (CBPs), whereas CASFM provides only CBPs. In addition, data have been collected from the results of different laboratory methods (Inhibition Zone diameters (IZD) from agar disk diffusion and Minimum Inhibition Concentrations (MIC) from various laboratory methods). Hence there is a network of combinations between laboratory methods, quantitative results and evaluation criteria.

Data have been managed and described using different tools such as the “Konstanz information Miner (KNIME)” tool and “R” software.

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