医院感染的扩展模型:参数估计和模型选择。

IF 0.8 4区 数学 Q4 BIOLOGY
Alun Thomas, Karim Khader, Andrew Redd, Molly Leecaster, Yue Zhang, Makoto Jones, Tom Greene, Matthew Samore
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引用次数: 10

摘要

我们考虑以几种方式扩展患者水平医院感染的先前模型,为这些新模型提供可能性规范,指定随机积分所需的新更新步骤,并提供实现这些方法的程序来获得参数估计和模型选择统计。先前的易感感染模型被扩展到允许在初始暴露于病原体和患者变得具有传染性之间的潜伏期,以及非殖民化的可能性。我们允许多个设施,如急性护理医院或长期护理设施和疗养院,以及设施内的多个单位或病房。在模型中跟踪和解释了单位和设施之间的患者转移,因此可以推断出从一个设施或单位直接输入殖民地个体到另一个设施或单位。我们允许恒定的传染率,传染率取决于单位或设施中定植个体的数量,或者取决于定植个体的比例。利用马尔可夫链蒙特卡罗方法在贝叶斯框架下进行统计分析,从参数值的联合后验分布中获得样本值。交叉验证、偏差信息标准和模型选择的广泛适用的信息标准方法非常自然地适合这个框架,我们已经实现了这三个方法。我们通过考虑模型选择问题和参数估计在退伍军人管理局医院的7个病房的1年耐甲氧西林金黄色葡萄球菌监测试验数据来说明我们的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Extended models for nosocomial infection: parameter estimation and model selection.

Extended models for nosocomial infection: parameter estimation and model selection.

Extended models for nosocomial infection: parameter estimation and model selection.

We consider extensions to previous models for patient level nosocomial infection in several ways, provide a specification of the likelihoods for these new models, specify new update steps required for stochastic integration, and provide programs that implement these methods to obtain parameter estimates and model choice statistics. Previous susceptible-infected models are extended to allow for a latent period between initial exposure to the pathogen and the patient becoming themselves infectious, and the possibility of decolonization. We allow for multiple facilities, such as acute care hospitals or long-term care facilities and nursing homes, and for multiple units or wards within a facility. Patient transfers between units and facilities are tracked and accounted for in the models so that direct importation of a colonized individual from one facility or unit to another might be inferred. We allow for constant transmission rates, rates that depend on the number of colonized individuals in a unit or facility, or rates that depend on the proportion of colonized individuals. Statistical analysis is done in a Bayesian framework using Markov chain Monte Carlo methods to obtain a sample of parameter values from their joint posterior distribution. Cross validation, deviance information criterion and widely applicable information criterion approaches to model choice fit very naturally into this framework and we have implemented all three. We illustrate our methods by considering model selection issues and parameter estimation for data on methicilin-resistant Staphylococcus aureus surveillance tests over 1 year at a Veterans Administration hospital comprising seven wards.

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来源期刊
CiteScore
2.20
自引率
0.00%
发文量
15
审稿时长
>12 weeks
期刊介绍: Formerly the IMA Journal of Mathematics Applied in Medicine and Biology. Mathematical Medicine and Biology publishes original articles with a significant mathematical content addressing topics in medicine and biology. Papers exploiting modern developments in applied mathematics are particularly welcome. The biomedical relevance of mathematical models should be demonstrated clearly and validation by comparison against experiment is strongly encouraged. The journal welcomes contributions relevant to any area of the life sciences including: -biomechanics- biophysics- cell biology- developmental biology- ecology and the environment- epidemiology- immunology- infectious diseases- neuroscience- pharmacology- physiology- population biology
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