网络流行病模型的模式动态与更高阶感染
Jiaojiao Guo1, Xing Li1, Runzi He1
1School of Mathematics, North University of China, Taiyuan 030051, Shanxi, China.
Chaos (Woodbury, N.Y.)
|October 23, 2024
概括
网络反应-扩散系统可以通过节点内的更高阶相互作用形成模式. 这项研究揭示了接触异质性如何影响这些模式和图灵不稳定性,有助于控制流行病.
科学领域:
- 数学生物学 数学生物学
- 网络科学 网络科学
- 复杂的系统复杂的系统.
背景情况:
- 目前关于反应扩散 (RD) 系统的研究往往忽视了节点内部的接触异质性.
- 反应术语中的更高阶相互作用对于理解复杂的模式形成至关重要.
研究的目的:
- 开发一个联网的 RD 模型,将高阶交互纳入简单复合体中.
- 研究接触异质性对图灵不稳定性和模式形成的影响.
主要方法:
- 网络 RD 模型的理论分析.
- 数字模拟用于探索模式动态.
- 分析网络结构与模式特征之间的关系.
主要成果:
- 高阶相互作用可以在网络 RD 系统中诱导图灵不稳定.
- 图灵不稳定范围与平均2个简数度的二次关系.
- 模式幅度显示了各种趋势,平均增加2个简单度,而感染密度持续上升.
结论:
- 节点内部的联系异质性显著影响网络 RD 系统中的模式形成.
- 调查结果提供了有关流行病动态的见解,并为预防策略提供了信息.
- 该研究强调了在研发和开发模型中考虑复杂的网络结构的重要性.
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