Preliminary analysis of the transmission dynamics of nosocomial infections: stochastic and management effects
Preliminary analysis of the transmission dynamics of nosocomial infections: stochastic and management effects
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DOI：
10.1053/jhin.1998.0647
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发表时间：
1999-10-01
影响因子：
6.9
通讯作者：
Scott, GM
中科院分区：
文献类型：
--
作者：
Cooper, BS;Medley, GF;Scott, GM
一个简单的数学模型，开发的手传医院病原体，如金黄色葡萄球菌在普通内科手术病房内的传播。与以前的模型相比，使用了随机方法。计算机模拟被用来探索该模型的属性，并在病原体的成功引入率，病房一级的患病率，和殖民化的病人天，强调在管理的病人和护理人员的变化的一般影响方面的结果。小的变化，在所有三个措施的有机体的可传播性导致大的变化。即使是有效洗手频率的小幅增加也足以控制地方性微生物。在各种不同的情况下，减少进入病房的殖民地病人的数量也是一种有效的控制措施。增加监测活动的成功引进率的影响不大，但殖民地的病人天和病房一级的患病率几乎呈线性下降。较短的患者住院时间伴随着较高的成功引进率，但对其他措施的影响不大，除非检测到一个殖民个体的平均时间是大相比，平均长度stay.We得出结论，机会效应可能是最重要的因素之一，在确定的过程中爆发。数学模型可以为少数过程之间的非线性相互作用提供有价值的见解，但对于医院病房中非常小的人群，随机方法是必不可少的。(C)1999年，医院感染协会。
A simple mathematical model is developed for the spread of hand-borne nosocomial pathogens such as Staphylococcus aureus within a general medical-surgical ward. In contrast to previous models a stochastic approach is used. Computer simulations are used to explore the properties of the model, and the results are presented in terms of the pathogen's successful introduction rate, ward-level prevalence, and colonized patient-days, emphasizing the general effects of changes in management of patients and carers.Small changes in the transmissibility of the organism resulted in large changes in all three measures. Even small increases in the frequency of effective handwashes were enough to bring endemic organisms under control. Reducing the number of colonized patients admitted to the ward was also an effective control measure across a wide range of different situations. Increasing surveillance activities had little effect on the successful introduction rate but gave an almost linear reduction in colonized patient-days and ward-level prevalence. Shorter lengths of patient stay were accompanied by higher successful introduction rates, but had little effect on the other measures unless the mean time before detection of a colonized individual was large compared to the mean length of stay.We conclude that chance effects are likely to be amongst the most important factors in determining the course of an outbreak. Mathematical models can provide valuable insights into the non-linear interactions between a small number of processes, but for the very small populations found in hospital wards, a stochastic approach is essential. (C) 1999 The Hospital Infection Society.