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Quantifying the Relationship between Antibiotic Use in Food-Producing Animals and Antibiotic Resistance in Humans
It is commonly asserted that agricultural production systems must use fewer antibiotics in food-producing animals in order to mitigate the global spread of antimicrobial resistance (AMR). In order to assess the cost-effectiveness of such interventions, especially given the potential trade-off with r...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8772955/ https://www.ncbi.nlm.nih.gov/pubmed/35052943 http://dx.doi.org/10.3390/antibiotics11010066 |
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author | Emes, David Naylor, Nichola Waage, Jeff Knight, Gwenan |
author_facet | Emes, David Naylor, Nichola Waage, Jeff Knight, Gwenan |
author_sort | Emes, David |
collection | PubMed |
description | It is commonly asserted that agricultural production systems must use fewer antibiotics in food-producing animals in order to mitigate the global spread of antimicrobial resistance (AMR). In order to assess the cost-effectiveness of such interventions, especially given the potential trade-off with rural livelihoods, we must quantify more precisely the relationship between food-producing animal antimicrobial use and AMR in humans. Here, we outline and compare methods that can be used to estimate this relationship, calling on key literature in this area. Mechanistic mathematical models have the advantage of being rooted in epidemiological theory, but may struggle to capture relevant non-epidemiological covariates which have an uncertain relationship with human AMR. We advocate greater use of panel regression models which can incorporate these factors in a flexible way, capturing both shape and scale variation. We provide recommendations for future panel regression studies to follow in order to inform cost-effectiveness analyses of AMR containment interventions across the One Health spectrum, which will be key in the age of increasing AMR. |
format | Online Article Text |
id | pubmed-8772955 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87729552022-01-21 Quantifying the Relationship between Antibiotic Use in Food-Producing Animals and Antibiotic Resistance in Humans Emes, David Naylor, Nichola Waage, Jeff Knight, Gwenan Antibiotics (Basel) Article It is commonly asserted that agricultural production systems must use fewer antibiotics in food-producing animals in order to mitigate the global spread of antimicrobial resistance (AMR). In order to assess the cost-effectiveness of such interventions, especially given the potential trade-off with rural livelihoods, we must quantify more precisely the relationship between food-producing animal antimicrobial use and AMR in humans. Here, we outline and compare methods that can be used to estimate this relationship, calling on key literature in this area. Mechanistic mathematical models have the advantage of being rooted in epidemiological theory, but may struggle to capture relevant non-epidemiological covariates which have an uncertain relationship with human AMR. We advocate greater use of panel regression models which can incorporate these factors in a flexible way, capturing both shape and scale variation. We provide recommendations for future panel regression studies to follow in order to inform cost-effectiveness analyses of AMR containment interventions across the One Health spectrum, which will be key in the age of increasing AMR. MDPI 2022-01-06 /pmc/articles/PMC8772955/ /pubmed/35052943 http://dx.doi.org/10.3390/antibiotics11010066 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Emes, David Naylor, Nichola Waage, Jeff Knight, Gwenan Quantifying the Relationship between Antibiotic Use in Food-Producing Animals and Antibiotic Resistance in Humans |
title | Quantifying the Relationship between Antibiotic Use in Food-Producing Animals and Antibiotic Resistance in Humans |
title_full | Quantifying the Relationship between Antibiotic Use in Food-Producing Animals and Antibiotic Resistance in Humans |
title_fullStr | Quantifying the Relationship between Antibiotic Use in Food-Producing Animals and Antibiotic Resistance in Humans |
title_full_unstemmed | Quantifying the Relationship between Antibiotic Use in Food-Producing Animals and Antibiotic Resistance in Humans |
title_short | Quantifying the Relationship between Antibiotic Use in Food-Producing Animals and Antibiotic Resistance in Humans |
title_sort | quantifying the relationship between antibiotic use in food-producing animals and antibiotic resistance in humans |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8772955/ https://www.ncbi.nlm.nih.gov/pubmed/35052943 http://dx.doi.org/10.3390/antibiotics11010066 |
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