标准差
统计
统计物理学
爆发
流行病模型
节点(物理)
数学
分布(数学)
异构网络
相(物质)
复杂网络
相变
计量经济学
物理
计算机科学
人口学
生物
凝聚态物理
数学分析
人口
量子力学
组合数学
病毒学
电信
无线网络
无线
社会学
作者
Xuzhen Zhu,Yuxin Wang,Ningbo Zhang,Hui Yang,Wei Wang
出处
期刊:Chaos
[American Institute of Physics]
日期:2022-08-01
卷期号:32 (8)
被引量:7
摘要
The spread of disease on complex networks has attracted wide attention in physics, mathematics, and epidemiology. Recent works have demonstrated that individuals always exhibit different criteria for disease infection in a network that significantly influences the epidemic dynamics. In this paper, considering the heterogeneity of node susceptibility, we proposed an infection threshold model with neighbor resource support. The infection threshold of an individual is associated with the degree, and a parameter follows the normal distribution. Based on improved heterogeneous mean-field theory and extensive numerical simulations, we find that the mean and standard deviation of the infection threshold model can affect the phase transition and epidemic outbreak size. As the mean of the normal distribution parameter increases from a small value to a large value, the system shows a change from a continuous phase transition to a discontinuous phase transition, and the disease even stops spreading. The disease spreads from a discontinuous phase transition to continuous for the sizeable mean value as the standard deviation increases. Furthermore, the standard deviation also varies in the outbreak size.
科研通智能强力驱动
Strongly Powered by AbleSci AI