MIC distribution analysis identifies differences in AMR between population sub-groups.

Background: Phenotypic data, such as the minimum inhibitory concentrations (MICs) of bacterial isolates from clinical samples, are widely available through routine surveillance. MIC distributions inform antibiotic dosing in clinical care by determining cutoffs to define isolates as susceptible or resistant. However, differences in MIC distributions between patient sub-populations could indicate strain variation and hence differences in transmission, infection, or selection. Methods: The Vivli AMR register contains a wealth of MIC and metadata for a vast range of bacteria-antibiotic combinations. Using a generalisable methodology followed by multivariate regression, we explored MIC distribution variations across 4 bacteria, covering 7,135,070 samples, by key population sub-groups such as age, sex and infection type, and over time. Results: We found clear differences between MIC distributions across various patient sub-groups for a subset of bacteria-antibiotic pairings. For example, within Conclusions: We found that MIC distributions can be used to identify differences in AMR levels between population sub-groups. Our methodology could be used more widely to unveil hidden transmission sources and effects of antibiotic use in different patient sub-groups, highlighting opportunities to improve stewardship programmes and interventions, particularly at local scales.