Bridging the Gaps: Systems-level approaches to antimicrobial resistance
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Bridging the Gaps: Systems-level approaches to antimicrobial resistance


Geospatial modelling the spread of AMR in the environment

Dov Stekel (Biosciences), Malcolm Bennett (School of Veterinary Medicine and Science) and Stuart Marsh (Engineering / Nottingham Geospatial Institute)

The issue

Currently our understanding of the spread of antimicrobial resistance (AMR) is limited to a small scale e.g. in an animal gut, a slurry tank, field soil or a wastewater treatment plant. If we can model AMR in the environment at a much larger scale then we will be better able to understand AMR, control it and react to any outbreaks. It is particularly difficult to develop predictive models of AMR because AMR, the organisms involved and the manner in which they operate, are all at a microscopic scale.

The research

Our researchers, tested a set of ideas that may later allow them to develop a larger scale model of AMR. These included: 

  1. The use of geospatial mapping. We want to understand AMR using real geographical space and to be able to predict AMR spread depending on what the land contains. For example we want to include information about sources of AMR (e.g. farms) and potential receptors (e.g. human populations).
  2. How rare events, such as resistance spreading between species, relates to predictable states, such as growth and competition between microbial populations. This will help us to bridge the microscopic and population-level scales.
  3. How we can combine information from geospatial AMR models with real environmental AMR data. Researchers used data gathered from wildlife and from The University of Nottingham farm. 

The impact

The long term goal of this work is to develop mathematical models that can predict the spread of AMR genes and organisms in the environment in space and time that can be used to inform policy and practice.

This would lead to three outcomes:

  • to inform general policy for control of AMR in agriculture and the environment;
  • to inform specific actions in the face of an outbreak of an AMR pathogen;
  • to inform empirical studies so that effective environmental survey of AMR organisms and genes can be designed.

Now that the pump prime phase of this project has completed the researcher, Hannah Williams, has moved on to a new role working as a mathematical modeller for Public Health England.  

If you are interested in finding out more about this research or about Bridging the Gaps please be in contact with Harry Moriarty in the first instance.

Bridging the Gaps: Antimicrobial Resistance

School of Mathematical Science
The University of Nottingham
University Park
Nottingham, NG7 2RD

telephone: +44 (0) 115 748 6317