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bioRxiv · 10.1101/2025.08.26.672312

A socio-ecological System Dynamics model of antimicrobial use and resistance

Redman-White, C. J.·Kopainsky, B.·Muwonge, A.·Peters, A. R.·Moran, D.
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Abstract

The concept of resource extraction in the context of antimicrobial resistance (AMR) is rarely explored. In this framework, antimicrobial susceptibility is viewed as a finite resource that is depleted through the use of antimicrobials --thus, AMR represents the exhaustion of this resource. In this work, we examine the system dynamics of AMR using causal loop diagrams to define both the structure and behaviour of two variants of the system. We then evaluate the robustness of the system dynamics models through sensitivity testing. The first model is inspired by a classic "Limits to Growth" structure, in which antimicrobial use practices depend on recent observations of treatment success or failure. The second differs by including AMR surveillance informing antimicrobial prescribing instead of anecdotal experience. The models consider one "bug-drug-mutation-context" combination at a time, but can be applied to different microbes, antimicrobials, and host populations in human or veterinary contexts. Multiparameter sensitivity analyses of relative fitness and timescale parameters were carried out on both model variants. Several key differences in model behaviour over time were observed between the socio-ecological Limits to Growth structure and the modified version in which human judgment, with its associated time lag, is bypassed. The models help explore the effects of human behaviour and associated time lags on patterns of population-level antimicrobial susceptibility over time, applying an established modelling technique in a novel context to generate new insights - notably that plateaux in AMR observed in the field could be in part due to human behaviour rather than purely evolutionary forces. The framing of antimicrobial susceptibility as a variably renewable natural resource is valuable not only as an avenue for alternative modelling approaches, but also as a more collaborative framing for public and policy engagement to promote sustainable management of this common pool resource.

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Redman-White, C. J., Kopainsky, B., Muwonge, A., Peters, A. R., Moran, D.. 2025-08-26. A socio-ecological System Dynamics model of antimicrobial use and resistance. https://doi.org/10.1101/2025.08.26.672312

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