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Approaches for quantifying antimicrobial consumption per animal species based on national sales data: a Swiss example, 2006 to 2013
Antimicrobial use in animals is known to contribute to the global burden of antimicrobial resistance. Therefore, it is critical to monitor antimicrobial sales for livestock and pets. Despite the availability of veterinary antimicrobial sales data in most European countries, surveillance currently la...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
European Centre for Disease Prevention and Control (ECDC)
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5316905/ https://www.ncbi.nlm.nih.gov/pubmed/28205504 http://dx.doi.org/10.2807/1560-7917.ES.2017.22.6.30458 |
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author | Carmo, Luís P Schüpbach-Regula, Gertraud Müntener, Cedric Chevance, Anne Moulin, Gérard Magouras, Ioannis |
author_facet | Carmo, Luís P Schüpbach-Regula, Gertraud Müntener, Cedric Chevance, Anne Moulin, Gérard Magouras, Ioannis |
author_sort | Carmo, Luís P |
collection | PubMed |
description | Antimicrobial use in animals is known to contribute to the global burden of antimicrobial resistance. Therefore, it is critical to monitor antimicrobial sales for livestock and pets. Despite the availability of veterinary antimicrobial sales data in most European countries, surveillance currently lacks consumption monitoring at the animal species level. In this study, alternative methods were investigated for stratifying antimicrobial sales per species using Swiss data (2006−2013). Three approaches were considered: (i) Equal Distribution (ED) allocated antimicrobial sales evenly across all species each product was licensed for; (ii) Biomass Distribution (BMD) stratified antimicrobial consumption, weighting the representativeness of each species' total biomass; and (iii) Longitudinal Study Extrapolation (LSE) assigned antimicrobial sales per species based on a field study describing prescription patterns in Switzerland. LSE is expected to provide the best estimates because it relies on field data. Given the Swiss example, BMD appears to be a reliable method when prescription data are not available, whereas ED seems to underestimate consumption in species with larger populations and higher treatment intensity. These methods represent a valuable tool for improving the monitoring systems of veterinary antimicrobial consumption across Europe. |
format | Online Article Text |
id | pubmed-5316905 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | European Centre for Disease Prevention and Control (ECDC) |
record_format | MEDLINE/PubMed |
spelling | pubmed-53169052017-02-28 Approaches for quantifying antimicrobial consumption per animal species based on national sales data: a Swiss example, 2006 to 2013 Carmo, Luís P Schüpbach-Regula, Gertraud Müntener, Cedric Chevance, Anne Moulin, Gérard Magouras, Ioannis Euro Surveill Research Article Antimicrobial use in animals is known to contribute to the global burden of antimicrobial resistance. Therefore, it is critical to monitor antimicrobial sales for livestock and pets. Despite the availability of veterinary antimicrobial sales data in most European countries, surveillance currently lacks consumption monitoring at the animal species level. In this study, alternative methods were investigated for stratifying antimicrobial sales per species using Swiss data (2006−2013). Three approaches were considered: (i) Equal Distribution (ED) allocated antimicrobial sales evenly across all species each product was licensed for; (ii) Biomass Distribution (BMD) stratified antimicrobial consumption, weighting the representativeness of each species' total biomass; and (iii) Longitudinal Study Extrapolation (LSE) assigned antimicrobial sales per species based on a field study describing prescription patterns in Switzerland. LSE is expected to provide the best estimates because it relies on field data. Given the Swiss example, BMD appears to be a reliable method when prescription data are not available, whereas ED seems to underestimate consumption in species with larger populations and higher treatment intensity. These methods represent a valuable tool for improving the monitoring systems of veterinary antimicrobial consumption across Europe. European Centre for Disease Prevention and Control (ECDC) 2017-02-09 /pmc/articles/PMC5316905/ /pubmed/28205504 http://dx.doi.org/10.2807/1560-7917.ES.2017.22.6.30458 Text en This article is copyright of The Authors, 2017. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0) Licence. You may share and adapt the material, but must give appropriate credit to the source, provide a link to the licence, and indicate if changes were made. |
spellingShingle | Research Article Carmo, Luís P Schüpbach-Regula, Gertraud Müntener, Cedric Chevance, Anne Moulin, Gérard Magouras, Ioannis Approaches for quantifying antimicrobial consumption per animal species based on national sales data: a Swiss example, 2006 to 2013 |
title | Approaches for quantifying antimicrobial consumption per animal species based on national sales data: a Swiss example, 2006 to 2013 |
title_full | Approaches for quantifying antimicrobial consumption per animal species based on national sales data: a Swiss example, 2006 to 2013 |
title_fullStr | Approaches for quantifying antimicrobial consumption per animal species based on national sales data: a Swiss example, 2006 to 2013 |
title_full_unstemmed | Approaches for quantifying antimicrobial consumption per animal species based on national sales data: a Swiss example, 2006 to 2013 |
title_short | Approaches for quantifying antimicrobial consumption per animal species based on national sales data: a Swiss example, 2006 to 2013 |
title_sort | approaches for quantifying antimicrobial consumption per animal species based on national sales data: a swiss example, 2006 to 2013 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5316905/ https://www.ncbi.nlm.nih.gov/pubmed/28205504 http://dx.doi.org/10.2807/1560-7917.ES.2017.22.6.30458 |
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