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

The study conceptualizes antimicrobial susceptibility as a finite, depletable resource, with antimicrobial resistance (AMR) representing its gradual exhaustion due to use. Using system dynamics models, the authors compare a traditional “Limits to Growth” scenario—where prescribing is based on recent treatment outcomes—with a model informed by AMR surveillance data. They show that human behaviour and decision-making delays play a critical role in shaping resistance patterns over time, and that incorporating surveillance can alter these dynamics. Notably, observed plateaux in AMR may partly stem from behavioural factors rather than purely biological evolution. This framing positions antimicrobial effectiveness as a common-pool resource, highlighting the need for data-driven stewardship and offering a compelling perspective for policy and public engagement.