Bodó Ágnes, Katona Gyula Y, Simon Péter L
Institute of Mathematics, Eötvös Loránd University Budapest, Budapest, Hungary.
Numerical Analysis and Large Networks Research Group, Hungarian Academy of Sciences, Budapest, Hungary.
Bull Math Biol. 2016 Apr;78(4):713-735. doi: 10.1007/s11538-016-0158-0. Epub 2016 Mar 31.
Mathematical modelling of epidemic propagation on networks is extended to hypergraphs in order to account for both the community structure and the nonlinear dependence of the infection pressure on the number of infected neighbours. The exact master equations of the propagation process are derived for an arbitrary hypergraph given by its incidence matrix. Based on these, moment closure approximation and mean-field models are introduced and compared to individual-based stochastic simulations. The simulation algorithm, developed for networks, is extended to hypergraphs. The effects of hypergraph structure and the model parameters are investigated via individual-based simulation results.
为了兼顾社区结构以及感染压力对受感染邻居数量的非线性依赖性,将网络上流行病传播的数学模型扩展到超图。根据由其关联矩阵给出的任意超图,推导了传播过程的精确主方程。在此基础上,引入了矩闭合近似和平均场模型,并与基于个体的随机模拟进行了比较。为网络开发的模拟算法被扩展到超图。通过基于个体的模拟结果研究了超图结构和模型参数的影响。