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Published June 10, 2021 | Version v1
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A report of AMR and AMU data (and data collection activities) in livestock and humans in the six participating countries, and with indication to its quality, comparability and purpose.

  • 1. BfR
  • 2. RKI

Description

Antimicrobial resistance (AMR) has become a serious and global threat to public health that requires
urgent actions all over the world. ARDIG is a One Health European Joint Programme (EJP) project
which is carried out under the need to increase knowledge about AMR (1). The project aims to
understand the dynamic of AMR by assessing national trends, Farm/hospital trends and isolate
trends from six different European countries (Spain, Norway, Germany, Netherlands, France and
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 epidemiological data from humans,
animals (especially cattle, poultry and pig), food and environment and data collection systems in the
5 EU countries, Norway and in Europe addressing the task 1.1. of WP1 ARDIG of exploring and
collecting data available on AMR and AMU.
Surveillance and monitoring systems are highly relevant to control AMU and AMR being one out of
five strategies of Global Action Plan (GAP) of WHO(2).
However, major challenges need to be faced up in order to harmonize data on AMU and AMR area.
Thus, AMR surveillance and monitoring systems vary substantially in the data type collected among
sectors such as antimicrobials tested, type of samples, sampling design, laboratory methods and
choice of breakpoints, analysis and reporting. Likewise, AMU data is difficult to obtain and AMU
collection systems are based on different sources such as sales or wholesale distribution, imports,
production, clinical or prescribing data (3).
The harmonization process between AMU and AMR, which entails a series of difficulties based on
characteristics previously defined, is of great relevance to enable to compare data.

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