Statistical epidemic modeling with hospital outbreak data
Statistical epidemic modeling with hospital outbreak data
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利用医院疫情数据进行统计流行病模型
DOI：
10.1002/sim.3419
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发表时间：
2008
影响因子：
2
通讯作者：
Johannes Huebner
中科院分区：
文献类型：
--
作者：
M. Wolkewitz;M. Dettenkofer;H. Bertz;M. Schumacher;Johannes Huebner
疫情数据分析有一个特点：个体具有高度依赖性，即感染病例是进一步感染病例的原因（交叉感染）。主要的流行病学参数是传播率：感染者与医院病房内其他患者密切接触导致定植或感染的比率。为了估计该参数，统计分析应基于描述流行病过程传播动态的适当区室模型。非参数方法适用于没有迁移的封闭人群，但特别是在医院，还必须考虑入院和出院。传输和放电必须被视为竞争事件。基于鞅的方法充分考虑了利率的时间相关特征，并产生了有用的估计。这些方法适用于德国弗莱堡大学医学中心肿瘤血液病房爆发的特定医院病原体耐万古霉素肠球菌 (VRE)。版权所有 © 2008 约翰·威利父子有限公司
The analysis of epidemic data has one special feature: individuals are highly dependent, i.e. infected cases are the cause of further infected cases (cross‐infection). The main epidemiological parameter of interest is the transmission rate: the rate with which an infectious individual has close contacts with other patients in the hospital unit resulting in colonization or infection. In order to estimate this parameter, the statistical analysis should be based on an appropriate compartmental model that describes the transmission dynamics of an epidemic process. Nonparametric methodology is available for closed populations without migration, but especially in hospitals, admission and discharge have to be taken into account in addition. Transmission and discharge have to be considered as competing events. Martingale‐based methodology takes the time‐dependent feature of the rates adequately into account and yields useful estimates. These methods are applied to an outbreak of the specific hospital pathogen vancomycin‐resistant enterococci (VRE) in an onco‐haematological unit at the University Medical Center Freiburg in Germany. Copyright © 2008 John Wiley & Sons, Ltd.