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细胞再生对病毒合并感染动态变化的影响。

The impact of cell regeneration on the dynamics of viral coinfection.

作者信息

Pinky Lubna, Dobrovolny Hana M

机构信息

Department of Physics and Astronomy, Texas Christian University, Fort Worth, Texas 76109, USA.

出版信息

Chaos. 2017 Jun;27(6):063109. doi: 10.1063/1.4985276.

Abstract

Many mathematical models of respiratory viral infections do not include regeneration of cells within the respiratory tract, arguing that the infection is resolved before there is significant cellular regeneration. However, recent studies have found that ∼40% of patients hospitalized with influenza-like illness are infected with at least two different viruses, which could potentially lead to longer-lasting infections. In these longer infections, cell regeneration might affect the infection dynamics, in particular, allowing for the possibility of chronic coinfections. Several mathematical models have been used to describe cell regeneration in infection models, though the effect of model choice on the predicted time course of viral coinfections is not clear. We investigate four mathematical models incorporating different mechanisms of cell regeneration during respiratory viral coinfection to determine the effect of cell regeneration on infection dynamics. We perform linear stability analysis for each of the models and find the steady states analytically. The analysis suggests that chronic illness is possible but only with one viral species; chronic coexistence of two different viral species is not possible with the regeneration models considered here.

摘要

许多呼吸道病毒感染的数学模型并未纳入呼吸道内细胞的再生情况,理由是在细胞大量再生之前感染就已得到解决。然而,近期研究发现,约40%因流感样疾病住院的患者感染了至少两种不同病毒,这可能导致感染持续时间更长。在这些持续时间更长的感染中,细胞再生可能会影响感染动态,特别是增加了慢性合并感染的可能性。已有若干数学模型用于描述感染模型中的细胞再生情况,不过模型选择对病毒合并感染预测时间进程的影响尚不清楚。我们研究了四个在呼吸道病毒合并感染期间纳入不同细胞再生机制的数学模型,以确定细胞再生对感染动态的影响。我们对每个模型进行线性稳定性分析,并通过解析方法找到稳态。分析表明,慢性病有可能发生,但仅针对一种病毒;在此处考虑的再生模型下,两种不同病毒的慢性共存是不可能的。

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