Garber A M
Department of Medicine, Stanford University School of Medicine, California 94305.
Theor Popul Biol. 1987 Dec;32(3):326-46. doi: 10.1016/0040-5809(87)90053-0.
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.
抗生素的使用常被指责为导致抗生素耐药菌感染患病率上升的原因。本文通过建立模型来描述具有不同抗生素敏感性的竞争性细菌菌株的生长，从而阐明抗生素暴露对细菌抗生素耐药性的影响。该分析将逻辑斯蒂增长模型进行了推广，纳入了作为抗生素水平任意函数的一阶增长参数。它推导出了种群大小、组成以及平均抗生素敏感性作为抗生素暴露函数的闭式解。在模型背景下分析了使细菌种群大小最小化的策略。这些启发式模型以形式化的方式探索了被认为是耐药性发展基础的种群动态。
