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...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
MDPI
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/171482 |
| _version_ | 1855532043344019456 |
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| author | Emes, David Naylor, Nichola R. Waage, Jeff Knight, Gwenan M. |
| author_browse | Emes, David Knight, Gwenan M. Naylor, Nichola R. Waage, Jeff |
| author_facet | Emes, David Naylor, Nichola R. Waage, Jeff Knight, Gwenan M. |
| author_sort | Emes, David |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| 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 | Journal Article |
| id | CGSpace171482 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI |
| publisherStr | MDPI |
| record_format | dspace |
| spelling | CGSpace1714822025-12-08T10:29:22Z Quantifying the relationship between antibiotic use in food-producing animals and antibiotic resistance in humans Emes, David Naylor, Nichola R. Waage, Jeff Knight, Gwenan M. resistance to antibiotics livestock agriculture antibiotics antimicrobials one health approach cost analysis 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. 2022 2025-01-29T12:58:14Z 2025-01-29T12:58:14Z Journal Article https://hdl.handle.net/10568/171482 en Open Access MDPI Emes, David; Naylor, Nichola; Waage, Jeff; and Knight, Gwenan. 2022. Quantifying the relationship between antibiotic use in food-producing animals and antibiotic resistance in humans. Antibiotics 11(1): 66. https://doi.org/10.3390/antibiotics11010066 |
| spellingShingle | resistance to antibiotics livestock agriculture antibiotics antimicrobials one health approach cost analysis Emes, David Naylor, Nichola R. Waage, Jeff Knight, Gwenan M. 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 | resistance to antibiotics livestock agriculture antibiotics antimicrobials one health approach cost analysis |
| url | https://hdl.handle.net/10568/171482 |
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