Evidence map›Paper›PMID 32308439›Full record

ArticleInfection and drug resistance2020

Monitoring Antimicrobial Resistance and Drug Usage in the Human and Livestock Sector and Foodborne Antimicrobial Resistance in Six European Countries.

Octavio Mesa Varona, Katerina Chaintarli, Berit Muller-Pebody, Muna F Anjum, Tim Eckmanns, Madelaine Norström, Ides Boone, Bernd-Alois Tenhagen

Open access · goldAbstract read
In one paragraph

Article in Infection and drug resistance, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
1.4field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 49 citations in OpenAlex.

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  13. Increasing proportions of extended-spectrum β-lactamase-producing isolates amongEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2023
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  17. PathogenicAntibiotics (Basel, Switzerland) · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 3 countries.

Octavio Mesa VaronaDepartment of Biological Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany.ORCID 0000-0001-7519-6931
Katerina ChaintarliDepartment of Bacteriology, Animal and Plant Health Agency (APHA), Addlestone, Surrey, UK.
Berit Muller-PebodyHealthcare-Associated Infections & Antimicrobial Resistance Division, National Infection Service, Public Health England (PHE), London, UK.ORCID 0000-0002-8874-480X
Muna F AnjumDepartment of Bacteriology, Animal and Plant Health Agency (APHA), Addlestone, Surrey, UK.
Tim EckmannsDepartment for Infectious Disease Epidemiology, Robert Koch Institute (RKI), Berlin, Germany.
Madelaine NorströmDepartment of Analysis and Diagnostics, Section of Epidemiology, Norwegian Veterinary Institute (NVI), Oslo, Norway.
Ides BooneDepartment for Infectious Disease Epidemiology, Robert Koch Institute (RKI), Berlin, Germany.ORCID 0000-0002-0962-3517
Bernd-Alois TenhagenDepartment of Biological Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany.
Animal and Plant Health Agency · GBFederal Institute for Risk Assessment · DERobert Koch Institute · DENorwegian Veterinary Institute · NOPublic Health England · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAntimicrobial 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.

methodsA literature search in 2018 was performed to identify relevant peer-reviewed articles and national and European grey reports as well as AMU/AMR databases.

resultsComparison 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.

Indexed as

AMRAMUfood-producing animalsharmonizationmonitoringsurveillance

Identifiers

PMID32308439
PMCPMC7140725
OpenAlexW3014252297

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.