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D-1.4. A report of the assessment of risk factors for AMR and AMU.Assessment of ecological and management factors associated with AMR and Antimicrobial usage

Mesa-Varona, O; Tenhagen, B-A

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        <foaf:name>Mesa-Varona, O</foaf:name>
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        <foaf:name>Tenhagen, B-A</foaf:name>
    <dct:title>D-1.4. A report of the assessment of risk factors for AMR and AMU.Assessment of ecological and management factors associated with AMR and Antimicrobial usage</dct:title>
    <dct:issued rdf:datatype="">2021</dct:issued>
    <dct:issued rdf:datatype="">2021-08-30</dct:issued>
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    <dct:description>&lt;p&gt;In previous deliverables (D 1.2. and D 1.3) resistance data of E. coli and antimicrobial use data collected from the human and the livestock sector in the ARDIG WP1 between 2014 and 2017 were described. Antimicrobial resistance data from livestock on non-clinical isolates are harmonized in Europe by the Decision 2013/652/EU and by the new Decision 2020/1729/EU that replaces the latter from 1 January 2021. On the other hand, data on clinical isolatesare not. Livestock data on AMR in clinical and non-clinical isolates, provided by the United Kingdom, Norway, France and Germany in the WP1 of ARDIG, are based ondifferent laboratory methodologies, different evaluation criteria (i.e. epidemiological vs. clinical), different antimicrobial susceptibility testing (AST) methods (e.g. disc diffusion or broth microdilution) and covering different antimicrobials and animal types. A first approach, performed in previous deliverables, was to transform quantitative resistance data from different laboratory methods and methodologies into qualitative data using specific standards (e.g. The European Committee for Antimicrobial Susceptibility Testing (EUCAST) and the French Society of Microbiology (CASFM)) and evaluation criteria(epidemiological or clinical). However, there will be still an issue with comparability of quantitative data from different methodologies applying this method.A further approach addressed in this delivery is to overcome the lack of AMR harmonizationon laboratory methods and methodologies using statistical methods on the quantitative data. This would allow comparing AMR data between and within countries.&lt;/p&gt;</dct:description>
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