论文标题
在聚集网络上竞争的两病模型
Two-pathogen model with competition on clustered networks
论文作者
论文摘要
网络提供了一个数学上丰富的框架，以代表足以传播疾病的社会接触。社交网络通常是高度聚集的，无法像本地树一样。在本文中，我们研究了在完整的跨免疫耦合下使用生成函数公式的聚类对病原体顺序菌株的传播的影响，从而导致了第二株共存阈值的条件。我们表明，聚类降低了第二株菌株的共存阈值及其在泊松网络中的暴发大小，同时对均匀度模型产生了相反的影响。我们得出的结论是，人口中的聚类必须提高第二波流行病分布在网络上的能力。我们将模型应用于多层聚类网络的研究，并在两个不同的传输性下观察残留图的破裂。
Networks provide a mathematically rich framework to represent social contacts sufficient for the transmission of disease. Social networks are often highly clustered and fail to be locally tree-like. In this paper, we study the effects of clustering on the spread of sequential strains of a pathogen using the generating function formulation under a complete cross-immunity coupling, deriving conditions for the threshold of coexistence of the second strain. We show that clustering reduces the coexistence threshold of the second strain and its outbreak size in Poisson networks, whilst exhibiting the opposite effects on uniform-degree models. We conclude that clustering within a population must increase the ability of the second wave of an epidemic to spread over a network. We apply our model to the study of multilayer clustered networks and observe the fracturing of the residual graph at two distinct transmissibilities.
