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Drivers of ESBL-producing Escherichia coli dynamics in calf fattening farms: A modelling study

The contribution of bacteria in livestock to the global burden of antimicrobial resistance raises concerns worldwide. However, the dynamics of selection and diffusion of antimicrobial resistance in farm animals are not fully understood. Here, we used veal calf fattening farms as a model system, as t...

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Autores principales: Bastard, Jonathan, Haenni, Marisa, Gay, Emilie, Glaser, Philippe, Madec, Jean-Yves, Temime, Laura, Opatowski, Lulla
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8022845/
https://www.ncbi.nlm.nih.gov/pubmed/33851002
http://dx.doi.org/10.1016/j.onehlt.2021.100238
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author Bastard, Jonathan
Haenni, Marisa
Gay, Emilie
Glaser, Philippe
Madec, Jean-Yves
Temime, Laura
Opatowski, Lulla
author_facet Bastard, Jonathan
Haenni, Marisa
Gay, Emilie
Glaser, Philippe
Madec, Jean-Yves
Temime, Laura
Opatowski, Lulla
author_sort Bastard, Jonathan
collection PubMed
description The contribution of bacteria in livestock to the global burden of antimicrobial resistance raises concerns worldwide. However, the dynamics of selection and diffusion of antimicrobial resistance in farm animals are not fully understood. Here, we used veal calf fattening farms as a model system, as they are a known reservoir of Extended Spectrum β-Lactamase-producing Escherichia coli (ESBL-EC). Longitudinal data of ESBL-EC carriage and antimicrobial use (AMU) were collected from three veal calf farms during the entire fattening process. We developed 18 agent-based mechanistic models to assess different hypotheses regarding the main drivers of ESBL-EC dynamics in calves. The models were independently fitted to the longitudinal data using Markov Chain Monte Carlo and the best model was selected. Within-farm transmission between individuals and sporadic events of contamination were found to drive ESBL-EC dynamics on farms. In the absence of AMU, the median carriage duration of ESBL-EC was estimated to be 19.6 days (95% credible interval: [12.7; 33.3]). In the best model, AMU was found to influence ESBL-EC dynamics, by affecting ESBL-EC clearance rather than acquisition. This effect of AMU was estimated to decrease gradually after the end of exposure and to disappear after 62.5 days [50.0; 76.9]. Moreover, using a simulation study, we quantified the efficacy of ESBL-EC mitigation strategies. Decreasing ESBL-EC prevalence by 50% on arrival at the fattening farm reduced prevalence at slaughter age by 33.3%. Completely eliminating the use of selective antibiotics on arrival had a strong effect on average ESBL-EC prevalence (relative reduction of 77.0%), but the effect was mild if this use was only decreased by 50% compared to baseline (relative reduction of 3.3%).
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spelling pubmed-80228452021-04-12 Drivers of ESBL-producing Escherichia coli dynamics in calf fattening farms: A modelling study Bastard, Jonathan Haenni, Marisa Gay, Emilie Glaser, Philippe Madec, Jean-Yves Temime, Laura Opatowski, Lulla One Health Research Paper The contribution of bacteria in livestock to the global burden of antimicrobial resistance raises concerns worldwide. However, the dynamics of selection and diffusion of antimicrobial resistance in farm animals are not fully understood. Here, we used veal calf fattening farms as a model system, as they are a known reservoir of Extended Spectrum β-Lactamase-producing Escherichia coli (ESBL-EC). Longitudinal data of ESBL-EC carriage and antimicrobial use (AMU) were collected from three veal calf farms during the entire fattening process. We developed 18 agent-based mechanistic models to assess different hypotheses regarding the main drivers of ESBL-EC dynamics in calves. The models were independently fitted to the longitudinal data using Markov Chain Monte Carlo and the best model was selected. Within-farm transmission between individuals and sporadic events of contamination were found to drive ESBL-EC dynamics on farms. In the absence of AMU, the median carriage duration of ESBL-EC was estimated to be 19.6 days (95% credible interval: [12.7; 33.3]). In the best model, AMU was found to influence ESBL-EC dynamics, by affecting ESBL-EC clearance rather than acquisition. This effect of AMU was estimated to decrease gradually after the end of exposure and to disappear after 62.5 days [50.0; 76.9]. Moreover, using a simulation study, we quantified the efficacy of ESBL-EC mitigation strategies. Decreasing ESBL-EC prevalence by 50% on arrival at the fattening farm reduced prevalence at slaughter age by 33.3%. Completely eliminating the use of selective antibiotics on arrival had a strong effect on average ESBL-EC prevalence (relative reduction of 77.0%), but the effect was mild if this use was only decreased by 50% compared to baseline (relative reduction of 3.3%). Elsevier 2021-03-18 /pmc/articles/PMC8022845/ /pubmed/33851002 http://dx.doi.org/10.1016/j.onehlt.2021.100238 Text en © 2021 The Authors. Published by Elsevier B.V. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Paper
Bastard, Jonathan
Haenni, Marisa
Gay, Emilie
Glaser, Philippe
Madec, Jean-Yves
Temime, Laura
Opatowski, Lulla
Drivers of ESBL-producing Escherichia coli dynamics in calf fattening farms: A modelling study
title Drivers of ESBL-producing Escherichia coli dynamics in calf fattening farms: A modelling study
title_full Drivers of ESBL-producing Escherichia coli dynamics in calf fattening farms: A modelling study
title_fullStr Drivers of ESBL-producing Escherichia coli dynamics in calf fattening farms: A modelling study
title_full_unstemmed Drivers of ESBL-producing Escherichia coli dynamics in calf fattening farms: A modelling study
title_short Drivers of ESBL-producing Escherichia coli dynamics in calf fattening farms: A modelling study
title_sort drivers of esbl-producing escherichia coli dynamics in calf fattening farms: a modelling study
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8022845/
https://www.ncbi.nlm.nih.gov/pubmed/33851002
http://dx.doi.org/10.1016/j.onehlt.2021.100238
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