Data from: Modelling the impact of curtailing antibiotic usage in food animals on antibiotic resistance in humans
van Bunnik, Bram A.D.
Woolhouse, Mark E.J.
van Bunnik, B. A. D., University of Edinburgh
Woolhouse, M. E. J., University of Edinburgh
Published Mar 07, 2017 on Dryad.
Cite this dataset
van Bunnik, Bram A.D.; Woolhouse, Mark E.J.; van Bunnik, B. A. D.; Woolhouse, M. E. J. (2017). Data from: Modelling the impact of curtailing antibiotic usage in food animals on antibiotic resistance in humans [Dataset]. Dryad. https://doi.org/10.5061/dryad.1g98m
Consumption of antibiotics in food animals is increasing worldwide and is approaching, if not already surpassing, the volume consumed by humans. It is often suggested that reducing the volume of antibiotics consumed by food animals could have public health benefits. Although this notion is widely regarded as intuitively obvious there is a lack of robust, quantitative evidence to either support or contradict the suggestion. As a first step towards addressing this knowledge gap, we develop a simple mathematical model for exploring the generic relationship between antibiotic consumption by food animals and levels of resistant bacterial infections in humans. We investigate the impact of restricting antibiotic consumption by animals and identify which model parameters most strongly determine that impact. Our results suggest that, for a wide range of scenarios, curtailing the volume of antibiotics consumed by food animals has, as a stand-alone measure, little impact on the level of resistance in humans. We also find that reducing the rate of transmission of resistance from animals to humans may be more effective than an equivalent reduction in the consumption of antibiotics in food animals. Moreover, the response to any intervention is strongly determined by the rate of transmission from humans to animals, an aspect which is rarely considered.
Mathematica notebook containing model and analysis
Mathemetica Notebook with the model description and analysis to create the Figures presented in the manuscript.
R Script for sensitivity analysis
R script for the sensitivity analysis as described in the manuscript