A Model to Investigate the Impact of Farm Practice on Antimicrobial Resistance in UK Dairy Farms

Lanyon, Christopher W.; King, John R.; Stekel, Dov J.; Gomes, Rachel L.

Abstract

© 2021, The Author(s). The ecological and human health impact of antibiotic use and the related antimicrobial resistance (AMR) in animal husbandry is poorly understood. In many countries, there has been considerable pressure to reduce overall antibiotic use in agriculture or to cease or minimise use of human critical antibiotics. However, a more nuanced approach would consider the differential impact of use of different antibiotic classes; for example, it is not known whether reduced use of bacteriostatic or bacteriolytic classes of antibiotics would be of greater value. We have developed an ordinary differential equation model to investigate the effects of farm practice on the spread and persistence of AMR in the dairy slurry tank environment. We model the chemical fate of bacteriolytic and bacteriostatic antibiotics within the slurry and their effect on a population of bacteria, which are capable of resistance to both types of antibiotic. Through our analysis, we find that changing the rate at which a slurry tank is emptied may delay the proliferation of multidrug-resistant bacteria by up to five years depending on conditions. This finding has implications for farming practice and the policies that influence waste management practices. We also find that, within our model, the development of multidrug resistance is particularly sensitive to the use of bacteriolytic antibiotics, rather than bacteriostatic antibiotics, and this may be cause for controlling the usage of bacteriolytic antibiotics in agriculture.

Citation

Lanyon, C. W., King, J. R., Stekel, D. J., & Gomes, R. L. (2021). A Model to Investigate the Impact of Farm Practice on Antimicrobial Resistance in UK Dairy Farms. Bulletin of Mathematical Biology, 83(4), Article 36. https://doi.org/10.1007/s11538-021-00865-9

• Journal Article Type: Article
• Acceptance Date: Feb 3, 2021
• Online Publication Date: Mar 1, 2021
• Publication Date: Apr 1, 2021
• Deposit Date: Mar 3, 2021
• Publicly Available Date: Mar 3, 2021
• Journal: Bulletin of Mathematical Biology
• Print ISSN: 0092-8240
• Electronic ISSN: 1522-9602
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 83
• Issue: 4
• Article Number: 36
• DOI: https://doi.org/10.1007/s11538-021-00865-9
• Keywords: Immunology; General Biochemistry, Genetics and Molecular Biology; Computational Theory and Mathematics; General Neuroscience; Pharmacology; General Agricultural and Biological Sciences; General Mathematics; General Environmental Science
• Public URL: https://nottingham-repository.worktribe.com/output/5364583
• Publisher URL: https://link.springer.com/article/10.1007/s11538-021-00865-9