Stochastic two-strain epidemic model with saturated incidence rates driven by Lévy noise

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Marya Sadki, Karam Allali
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引用次数: 0

Abstract

In this paper, we introduce a stochastic two-strain epidemic model driven by Lévy noise describing the interaction between four compartments; susceptible, infected individuals by the first strain, infected ones by the second strain and the recovered individuals. The forces of infection, for both strains, are represented by saturated incidence rates. Our study begins with the investigation of unique global solution of the suggested mathematical model. Then, it moves to the determination of sufficient conditions of extinction and persistence in mean of the two-strain disease. In order to illustrate the theoretical findings, we give some numerical simulations.

莱维噪声驱动饱和发病率的双菌株随机流行病模型。
在本文中,我们引入了一个由勒维噪声驱动的随机双菌株流行病模型,该模型描述了四个部分之间的相互作用:易感者、被第一菌株感染的个体、被第二菌株感染的个体以及康复个体。两种菌株的感染力由饱和发病率表示。我们的研究从研究建议数学模型的唯一全局解开始。然后,再确定双菌株疾病平均消亡和持续存在的充分条件。为了说明理论结论,我们进行了一些数值模拟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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