Department of Mathematics and Statistics, University of Victoria, Victoria, BC, Canada.
J Math Biol. 2022 Jun 12;84(7):59. doi: 10.1007/s00285-022-01764-w.
The effective degree SIR model describes the dynamics of diseases with lifetime acquired immunity on a static random contact network. It is typically modeled as a system of ordinary differential equations describing the probability distribution of the infection status of neighbors of a susceptible node. Such a construct may not be used to study networks with an infinite degree distribution, such as an infinite scale-free network. We propose a new generating function approach to rewrite the effective degree SIR model as a nonlinear transport type partial differential equation. We show the existence and uniqueness of the solutions the are biologically relevant. In addition we show how this model may be reduced to the Volz model with the assumption that the infection statuses of the neighbors of an susceptible node are initially independent to each other. This paper paves the way to study the stability of the disease-free steady state and the disease threshold of the infinite dimensional effective degree SIR models.
有效度 SIR 模型描述了具有终身获得性免疫的疾病在静态随机接触网络上的动力学。它通常被建模为一个描述易感染节点邻居感染状态概率分布的常微分方程系统。这种结构可能不适用于研究具有无限度数分布的网络,例如无限无标度网络。我们提出了一种新的生成函数方法,将有效度 SIR 模型重写为非线性输运型偏微分方程。我们证明了在生物学上相关的解的存在性和唯一性。此外,我们还展示了如何在假设易感染节点的邻居的感染状态在初始时是相互独立的情况下,将该模型简化为 Volz 模型。本文为研究无限维有效度 SIR 模型的无病平衡点和疾病阈值的稳定性铺平了道路。