Antibiotic exposure and resistance in mixed bacterial populations.
Antibiotic use is often blamed for increases in the prevalence of infections due to antibiotic-resistance bacteria. This paper clarifies the effects of antibiotic exposure on bacterial antibiotic resistance by developing models that describe the growth of competing bacterial strains whose antibiotic sensitivities differ. The analysis generalizes logistic growth models to include first-order growth parameters that are arbitrary functions of antibiotic levels. It derives closed-form solutions for population size, composition, and average antibiotic sensitivities as functions of antibiotic exposure. Strategies to minimize the bacterial population size are analyzed in the context of the model. These heuristic models explore in formal terms the population dynamics thought to underlie resistance development.
Department of Medicine, Stanford University School of Medicine, California 94305.
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AM
Garber
D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D001419:Bacteria / Q000187:drug effects* / Q000235:genetics; D018407:Bacterial Physiological Phenomena; D004352:Drug Resistance, Microbial; D008954:Models, Biological
D000900:Anti-Bacterial Agents