The human microbiome can protect against colonization with pathogenic antibiotic-resistant bacteria (ARB), but its impacts on the spread of antibiotic resistance are poorly understood. We propose a mathematical modelling framework for ARB epidemiology formalizing within-host ARB-microbiome competition, and impacts of antibiotic consumption on microbiome function. Applied to the healthcare setting, we demonstrate a trade-off whereby antibiotics simultaneously clear bacterial pathogens and increase host susceptibility to their colonization, and compare this framework with a traditional strain-based approach. At the population level, microbiome interactions drive ARB incidence, but not resistance rates, reflecting distinct epidemiological relevance of different forces of competition. Simulating a range of public health interventions (contact precautions, antibiotic stewardship, microbiome recovery therapy) and pathogens (Clostridioides difficile, methicillin-resistant Staphylococcus aureus, multidrug-resistant Enterobacteriaceae) highlights how species-specific within-host ecological interactions drive intervention efficacy. We find limited impact of contact precautions for Enterobacteriaceae prevention, and a promising role for microbiome-targeted interventions to limit ARB spread.
Model equations and parameter values are provided in the manuscript, as well as in supporting R files and a Mathematica notebook available online at https://github.com/drmsmith/microbiomeR
- David R M Smith
- David R M Smith
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Gwenan M Knight, London School of Hygiene and Tropical Medicine, United Kingdom
- Received: March 26, 2021
- Accepted: August 31, 2021
- Accepted Manuscript published: September 14, 2021 (version 1)
© 2021, Smith et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.