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甲型流感抗原漂移模型中的行波

Traveling waves in a model of influenza A drift.

作者信息

Lin Juan, Andreasen Viggo, Casagrandi Renato, Levin Simon A

机构信息

Department of Physics, Washington College, 3000 Washington Avenue, Chestertown, MD 21620, USA.

出版信息

J Theor Biol. 2003 Jun 21;222(4):437-45. doi: 10.1016/s0022-5193(03)00056-0.

Abstract

Between major pandemics, the influenza A virus changes its antigenic properties by accumulating point mutations (drift) mainly in the RNA genes that code for the surface proteins hemagglutinin (HA) and neuraminidase (NA). The successful strain (variant) that will cause the next epidemic is selected from a reduced number of progenies that possess relatively high transmissibility and the ability to escape from the immune surveillance of the host. In this paper, we analyse a one-dimensional model of influenza A drift (Z. Angew. Math. Mech. 76 (2) (1996) 421) that generalizes the classical SIR model by including mutation as a diffusion process in a phenotype space of variants. The model exhibits traveling wave solutions with an asymptotic wave speed that matches well those obtained from numerical simulations. As exact solutions for these waves are not available, asymptotic estimates for the amplitudes of infected and recovered classes are provided through an exponential approximation based on the smallness of the diffusion constant. Through this approximation, we find simple scaling properties to several parameters of relevance to the epidemiology of the disease.

摘要

在大流行期间,甲型流感病毒通过主要在编码表面蛋白血凝素(HA)和神经氨酸酶(NA)的RNA基因中积累点突变(漂移)来改变其抗原特性。导致下一次流行的成功毒株(变体)是从数量减少的后代中挑选出来的,这些后代具有相对较高的传播性以及逃避宿主免疫监视的能力。在本文中,我们分析了一个甲型流感病毒漂移的一维模型(《应用数学与力学杂志》76 (2) (1996) 421),该模型通过将突变作为变体表型空间中的扩散过程纳入,推广了经典的SIR模型。该模型展现出行波解,其渐近波速与数值模拟得到的波速非常匹配。由于这些波的精确解不可得,基于扩散常数的微小性,通过指数近似提供了感染类和恢复类振幅的渐近估计。通过这种近似,我们发现了与该疾病流行病学相关的几个参数的简单标度性质。

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