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随机和确定性流行病模型中的接触者追踪

Contact tracing in stochastic and deterministic epidemic models.

作者信息

Müller J, Kretzschmar M, Dietz K

机构信息

Biomathematik, Universität Tübingen, Auf der Morgenstelle 10, D-72076, Tübingen, Germany.

出版信息

Math Biosci. 2000 Mar;164(1):39-64. doi: 10.1016/s0025-5564(99)00061-9.

Abstract

We consider a simple unstructured individual based stochastic epidemic model with contact tracing. Even in the onset of the epidemic, contact tracing implies that infected individuals do not act independent of each other. Nevertheless, it is possible to analyze the embedded non-stationary Galton-Watson process. Based upon this analysis, threshold theorems and also the probability for major outbreaks can be derived. Furthermore, it is possible to obtain a deterministic model that approximates the stochastic process, and in this way, to determine the prevalence of disease in the quasi-stationary state and to investigate the dynamics of the epidemic.

摘要

我们考虑一个简单的基于个体的无结构随机传染病模型,并带有接触者追踪。即使在疫情初期,接触者追踪意味着受感染个体并非相互独立行动。然而,仍有可能分析其中嵌入的非平稳高尔顿-沃森过程。基于此分析,可以推导出阈值定理以及重大疫情爆发的概率。此外,还能够得到一个近似该随机过程的确定性模型,通过这种方式来确定准稳态下的疾病流行程度,并研究疫情的动态变化。

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