由潜伏期、感染期和免疫期决定的延迟流行模型

IF 1.9 4区 数学 Q2 BIOLOGY Mathematical Biosciences Pub Date : 2024-02-03 DOI:10.1016/j.mbs.2024.109155
Masoud Saade , Samiran Ghosh , Malay Banerjee , Vitaly Volpert
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引用次数: 0

摘要

我们提出了新的单株和双株流行病模型,这些模型由延迟微分方程系统表示,并基于新暴露个体的数量。暴露区、感染区、恢复区和回到易感区之间的转换由相应的时间延迟决定。证明了解的存在性和实在性。将延迟微分方程还原为积分方程,可以分析静态解及其稳定性。在两个菌株的情况下,它们会相互竞争,个体基本繁殖数较大的菌株会支配另一个菌株。然而,如果基本繁殖数超过某些临界值,静止解就会失去稳定性,导致周期性时间振荡。在这种情况下,两种应变都存在,它们的动态并不完全由基本繁殖数决定,还受其他参数的影响。通过与季节性流感数据的比较,说明了这项工作的结果。
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Delay epidemic models determined by latency, infection, and immunity duration

We propose new single and two-strain epidemic models represented by systems of delay differential equations and based on the number of newly exposed individuals. Transitions between exposed, infectious, recovered, and back to susceptible compartments are determined by the corresponding time delays. Existence and positiveness of solutions are proved. Reduction of delay differential equations to integral equations allows the analysis of stationary solutions and their stability. In the case of two strains, they compete with each other, and the strain with a larger individual basic reproduction number dominates the other one. However, if the basic reproduction number exceeds some critical values, stationary solution loses its stability resulting in periodic time oscillations. In this case, both strains are present and their dynamics is not completely determined by the basic reproduction numbers but also by other parameters. The results of the work are illustrated by comparison with data on seasonal influenza.

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来源期刊
Mathematical Biosciences
Mathematical Biosciences 生物-生物学
CiteScore
7.50
自引率
2.30%
发文量
67
审稿时长
18 days
期刊介绍: Mathematical Biosciences publishes work providing new concepts or new understanding of biological systems using mathematical models, or methodological articles likely to find application to multiple biological systems. Papers are expected to present a major research finding of broad significance for the biological sciences, or mathematical biology. Mathematical Biosciences welcomes original research articles, letters, reviews and perspectives.
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