Monitoring Antimicrobial Resistance and Drug Usage in the Human and Livestock Sector and Foodborne Antimicrobial Resistance in Six European Countries
Received 1 November 2019
Accepted for publication 26 February 2020
Published 3 April 2020 Volume 2020:13 Pages 957—993
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Eric Nulens
Octavio Mesa Varona,1 Katerina Chaintarli,2 Berit Muller-Pebody,3 Muna F Anjum,2 Tim Eckmanns,4 Madelaine Norström,5 Ides Boone,4 Bernd-Alois Tenhagen1
1Department of Biological Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany; 2Department of Bacteriology, Animal and Plant Health Agency (APHA), Addlestone, Surrey, UK; 3Healthcare-Associated Infections & Antimicrobial Resistance Division, National Infection Service, Public Health England (PHE), London, UK; 4Department for Infectious Disease Epidemiology, Robert Koch Institute (RKI), Berlin, Germany; 5Department of Analysis and Diagnostics, Section of Epidemiology, Norwegian Veterinary Institute (NVI), Oslo, Norway
Correspondence: Octavio Mesa Varona Diedersdorfer Weg 1, Berlin 12277, Germany
Tel +49 30 1841224338
Introduction: Antimicrobial resistance (AMR), associated with antimicrobial use (AMU), is a major public concern. Surveillance and monitoring systems are essential to assess and control the trends in AMU and AMR. However, differences in the surveillance and monitoring systems between countries and sectors make comparisons challenging. The purpose of this article is to describe all surveillance and monitoring systems for AMU and AMR in the human and livestock sectors, as well as national surveillance and monitoring systems for AMR in food, in six European countries (Spain, Germany, France, the Netherlands, the United Kingdom and Norway) as a baseline for developing suggestions to overcome current limitations in comparing AMU and AMR data.
Methods: A literature search in 2018 was performed to identify relevant peer-reviewed articles and national and European grey reports as well as AMU/AMR databases.
Results: Comparison of AMU and AMR systems across the six countries showed a lack of standardization and harmonization with different AMU data sources (prescription vs sales data) and units of AMU and AMR being used. The AMR data varied by sample type (clinical/non-clinical), laboratory method (disk diffusion, microdilution, and VITEK, among others), data type, ie quantitative (minimum inhibition concentration (MIC) in mg/L/inhibition zone (IZ) in mm) vs qualitative data (susceptible-intermediate-resistant (SIR)), the standards used (EUCAST/CLSI among others), and/or the evaluation criteria adopted (epidemiological or clinical).
Discussion: A One Health approach for AMU and AMR requires harmonization in various aspects between human, animal and food systems at national and international levels. Additionally, some overlap between systems of AMU and AMR has been encountered. Efforts should be made to improve standardization and harmonization and allow more meaningful analyses of AMR and AMU surveillance data under a One Health approach.
Keywords: AMR, AMU, food-producing animals, harmonization, monitoring, surveillance
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