DataSheet2_Building a network with assortative mixing starting from preference functions, with application to the spread of epidemics.pdf

Compartmental models of disease spread have been well studied on networks built according to the Configuration Model, i.e., where the degree distribution of individual nodes is specified, but where connections are made randomly. Dynamics of spread on such “first order” networks were shown to be profoundly different compared to epidemics under the traditional mass action assumption. Assortativity, i.e., the preferential mixing of nodes according to degree, is a second order property that is thought to impact epidemic trajectory. We first show how assortative mixing can come about from individual preferences to connect with others of lower or higher degree, and propose an algorithm for constructing such a network. We then investigate via simulation how this network structure favors or inhibits diffusion processes, such as the spread of an infectious disease.

传染病传播仓室模型（Compartmental Model）已在基于配置模型（Configuration Model）构建的网络上得到充分研究——这类网络预先设定单个节点的度分布（degree distribution），却随机生成节点间的连接。已有研究证实，此类“一阶”网络上的传播动力学，与传统质量作用假设下的传染病传播动力学存在显著差异。同配性（Assortativity），即依据节点度值进行偏好性连接的属性，是一种被认为会影响传染病传播轨迹的二阶网络属性。我们首先阐释了同配性连接如何源于节点优先连接度值更高或更低的其他节点的个体偏好，并提出了一种构建此类网络的算法。随后我们通过模拟实验，探究了该网络结构对传染病传播等扩散过程的促进或抑制作用。