具有 SIR 型感染的排队系统

IF 0.7 3区 工程技术 Q4 ENGINEERING, INDUSTRIAL Probability in the Engineering and Informational Sciences Pub Date : 2024-01-16 DOI:10.1017/s0269964823000256
Claude Lefèvre, Matthieu Simon
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引用次数: 0

摘要

我们考虑的是随机 SIR 型流行病在两个相连种群中的传播问题:一个相对较小的本地相关种群被一个大得多的外部种群所包围。外部感染者可以暂时进入小种群,并促进感染在该种群内部的传播。感染者进入小群体的规则及其停留时间由一般马尔可夫排队系统建模。我们的主要目标是确定两个人群中感染者总数的分布情况。为此,我们提出的方法包括为联合流行过程推导出一系列马氏过程,并应用经典的停止时间或收敛定理。然后,研究将重点放在外部感染由线性分支过程描述且外部感染者的进入遵守某些特定规则的几种特殊情况上。一些结果通过数值示例进行了说明。
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A queueing system with an SIR-type infection

We consider the propagation of a stochastic SIR-type epidemic in two connected populations: a relatively small local population of interest which is surrounded by a much larger external population. External infectives can temporarily enter the small population and contribute to the spread of the infection inside this population. The rules for entry of infectives into the small population as well as their length of stay are modeled by a general Markov queueing system. Our main objective is to determine the distribution of the total number of infections within both populations. To do this, the approach we propose consists of deriving a family of martingales for the joint epidemic processes and applying classical stopping time or convergence theorems. The study then focuses on several particular cases where the external infection is described by a linear branching process and the entry of external infectives obeys certain specific rules. Some of the results obtained are illustrated by numerical examples.

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来源期刊
CiteScore
2.20
自引率
18.20%
发文量
45
审稿时长
>12 weeks
期刊介绍: The primary focus of the journal is on stochastic modelling in the physical and engineering sciences, with particular emphasis on queueing theory, reliability theory, inventory theory, simulation, mathematical finance and probabilistic networks and graphs. Papers on analytic properties and related disciplines are also considered, as well as more general papers on applied and computational probability, if appropriate. Readers include academics working in statistics, operations research, computer science, engineering, management science and physical sciences as well as industrial practitioners engaged in telecommunications, computer science, financial engineering, operations research and management science.
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