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

Bull Math Biol. 2021 Mar 1;83(4):36. doi: 10.1007/s11538-021-00865-9.

Abstract

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.

Keywords: Agriculture; Antibiotics; Antimicrobial resistance; Modelling; Ordinary differential equations; Slurry.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animal Husbandry* / methods
  • Animals
  • Anti-Bacterial Agents / pharmacology
  • Bacteria / drug effects
  • Dairying* / methods
  • Drug Resistance, Bacterial*
  • Farms / statistics & numerical data
  • Models, Biological*
  • United Kingdom

Substances

  • Anti-Bacterial Agents