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Detection of Rare Antimicrobial Resistance Profiles by Active and Passive Surveillance Approaches

Antimicrobial resistance (AMR) surveillance systems are generally not specifically designed to detect emerging resistances and usually focus primarily on resistance to individual drugs. Evaluating the diversity of resistance, using ecological metrics, allows the assessment of sampling protocols with...

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Autores principales: Mather, Alison E., Reeve, Richard, Mellor, Dominic J., Matthews, Louise, Reid-Smith, Richard J., Dutil, Lucie, Haydon, Daniel T., Reid, Stuart W. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4938605/
https://www.ncbi.nlm.nih.gov/pubmed/27391966
http://dx.doi.org/10.1371/journal.pone.0158515
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author Mather, Alison E.
Reeve, Richard
Mellor, Dominic J.
Matthews, Louise
Reid-Smith, Richard J.
Dutil, Lucie
Haydon, Daniel T.
Reid, Stuart W. J.
author_facet Mather, Alison E.
Reeve, Richard
Mellor, Dominic J.
Matthews, Louise
Reid-Smith, Richard J.
Dutil, Lucie
Haydon, Daniel T.
Reid, Stuart W. J.
author_sort Mather, Alison E.
collection PubMed
description Antimicrobial resistance (AMR) surveillance systems are generally not specifically designed to detect emerging resistances and usually focus primarily on resistance to individual drugs. Evaluating the diversity of resistance, using ecological metrics, allows the assessment of sampling protocols with regard to the detection of rare phenotypes, comprising combinations of resistances. Surveillance data of phenotypic AMR of Canadian poultry Salmonella Heidelberg and swine Salmonella Typhimurium var. 5- were used to contrast active (representative isolates derived from healthy animals) and passive (diagnostic isolates) surveillance and assess their suitability for detecting emerging resistance patterns. Although in both datasets the prevalences of resistance to individual antimicrobials were not significantly different between the two surveillance systems, analysis of the diversity of entire resistance phenotypes demonstrated that passive surveillance of diagnostic isolates detected more unique phenotypes. Whilst the most appropriate surveillance method will depend on the relevant objectives, under the conditions of this study, passive surveillance of diagnostic isolates was more effective for the detection of rare and therefore potentially emerging resistance phenotypes.
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spelling pubmed-49386052016-07-22 Detection of Rare Antimicrobial Resistance Profiles by Active and Passive Surveillance Approaches Mather, Alison E. Reeve, Richard Mellor, Dominic J. Matthews, Louise Reid-Smith, Richard J. Dutil, Lucie Haydon, Daniel T. Reid, Stuart W. J. PLoS One Research Article Antimicrobial resistance (AMR) surveillance systems are generally not specifically designed to detect emerging resistances and usually focus primarily on resistance to individual drugs. Evaluating the diversity of resistance, using ecological metrics, allows the assessment of sampling protocols with regard to the detection of rare phenotypes, comprising combinations of resistances. Surveillance data of phenotypic AMR of Canadian poultry Salmonella Heidelberg and swine Salmonella Typhimurium var. 5- were used to contrast active (representative isolates derived from healthy animals) and passive (diagnostic isolates) surveillance and assess their suitability for detecting emerging resistance patterns. Although in both datasets the prevalences of resistance to individual antimicrobials were not significantly different between the two surveillance systems, analysis of the diversity of entire resistance phenotypes demonstrated that passive surveillance of diagnostic isolates detected more unique phenotypes. Whilst the most appropriate surveillance method will depend on the relevant objectives, under the conditions of this study, passive surveillance of diagnostic isolates was more effective for the detection of rare and therefore potentially emerging resistance phenotypes. Public Library of Science 2016-07-08 /pmc/articles/PMC4938605/ /pubmed/27391966 http://dx.doi.org/10.1371/journal.pone.0158515 Text en © 2016 Mather et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Mather, Alison E.
Reeve, Richard
Mellor, Dominic J.
Matthews, Louise
Reid-Smith, Richard J.
Dutil, Lucie
Haydon, Daniel T.
Reid, Stuart W. J.
Detection of Rare Antimicrobial Resistance Profiles by Active and Passive Surveillance Approaches
title Detection of Rare Antimicrobial Resistance Profiles by Active and Passive Surveillance Approaches
title_full Detection of Rare Antimicrobial Resistance Profiles by Active and Passive Surveillance Approaches
title_fullStr Detection of Rare Antimicrobial Resistance Profiles by Active and Passive Surveillance Approaches
title_full_unstemmed Detection of Rare Antimicrobial Resistance Profiles by Active and Passive Surveillance Approaches
title_short Detection of Rare Antimicrobial Resistance Profiles by Active and Passive Surveillance Approaches
title_sort detection of rare antimicrobial resistance profiles by active and passive surveillance approaches
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4938605/
https://www.ncbi.nlm.nih.gov/pubmed/27391966
http://dx.doi.org/10.1371/journal.pone.0158515
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