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随机树接触追踪的精确和近似公式。

Exact and approximate formulas for contact tracing on random trees.

机构信息

Center for Mathematical Sciences, Technische Universität München, Garching 85748, Germany.

Center for Mathematical Sciences, Technische Universität München, Garching 85748, Germany; Institute for Computational Biology, Helmholtz Center Munich, Neuherberg 85764, Germany.

出版信息

Math Biosci. 2020 Mar;321:108320. doi: 10.1016/j.mbs.2020.108320. Epub 2020 Jan 31.

Abstract

We consider a stochastic susceptible-infected-recovered (SIR) model with contact tracing on random trees and on the configuration model. On a rooted tree, where initially all individuals are susceptible apart from the root which is infected, we are able to find exact formulas for the distribution of the infectious period. Thereto, we show how to extend the existing theory for contact tracing in homogeneously mixing populations to trees. Based on these formulas, we discuss the influence of randomness in the tree and the basic reproduction number. We find the well known results for the homogeneously mixing case as a limit of the present model (tree-shaped contact graph). Furthermore, we develop approximate mean field equations for the dynamics on trees, and - using the message passing method - also for the configuration model. The interpretation and implications of the results are discussed.

摘要

我们考虑了带有接触追踪的随机易感染者-感染者-恢复者(SIR)模型,分别在随机树和配置模型上进行了研究。在有根树中,除了根节点感染外,所有个体初始均易感,我们能够为感染期分布找到精确的公式。为此,我们展示了如何将同质混合群体中现有的接触追踪理论扩展到树中。基于这些公式,我们讨论了树中随机性和基本再生数的影响。我们发现了同质混合情况下的著名结果是当前模型(树状接触图)的极限。此外,我们还为树状动力学开发了近似均值场方程,并使用消息传递方法也为配置模型开发了方程。讨论了结果的解释和影响。

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