Impact of Resistance Development Mechanisms on Antibiotic Treatment Outcomes
Ailin Zhang, Shigui Ruan, and Xi Huo

TL;DR
This study uses mathematical models to analyze how different bacterial resistance mechanisms influence antibiotic treatment success, revealing that plasmid-mediated resistance favors fixed dosing, while mutation-driven resistance complicates treatment outcomes.
Contribution
It provides a comparative analysis of resistance mechanisms' impact on treatment efficacy using stability analysis and simulations, informing optimal dosing strategies.
Findings
Fixed dosing is more effective against plasmid-mediated resistance.
Mutation-driven resistance leads to higher likelihood of resistant strains after treatment failure.
Twice-daily regimens outperform once-daily in clearing infections.
Abstract
Bacteria develop resistance to antibiotics through various mechanisms, with the specific mechanism depending on the drug-bacteria pair. It remains unclear, however, which resistance mechanism best supports favorable treatment outcomes, specifically in clearing infections and inhibiting further resistance. In this study, we use periodic ordinary differential equation models to simulate different antibiotic treatment protocols for bacterial infections. Using stability analysis and numerical simulations, we investigate how different resistance mechanisms, including plasmid-induced and mutation-induced resistance, affect treatment outcomes. Our findings suggest that antibiotic treatments with fixed dosing schedules are more likely to be effective when resistance arises exclusively through plasmid-mediated transmission. Further, when treatment fails, mutation-driven mechanisms tend to favor…
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Taxonomy
TopicsEvolution and Genetic Dynamics · Mathematical and Theoretical Epidemiology and Ecology Models · Antibiotic Use and Resistance
