复制高图的疾病动态与较低阶相互作用
Eugene Tan1, Michael Small2, Shannon D Algar2
1The Kids Research Institute Australia, Nedlands 6009, Australia.
Physical review. E
|February 20, 2026
概括
疾病传播模型可以通过调整简单模型中的参数来模拟复杂的网络动态. 这项研究统一了分隔和简化传染模型,表明双向相互作用可以复制更高阶效应.
科学领域:
- 流行病学 流行病学
- 网络科学 网络科学
- 计算建模 计算建模
背景情况:
- 像SIS/SIR这样的分支模型是流行病和信息传播研究的标准.
- 网络结构通过模拟对对互动来增强现实性.
- 简单传染模型 (SCM) 使用高阶相互作用 (组>2) 的超图.
研究的目的:
- 统一经典的分隔模型与简化的传染模型.
- 将模型扩展到任意顺序的超边界相互作用.
- 为了调查更高阶相互作用是否产生从根本上不同的动态,而不是双对相互作用.
主要方法:
- 开发了一个基于代理的模型,将SIS/SIR和SCM统一起来.
- 扩展了对任何顺序的超边缘相互作用的模型.
- 通过缩放的对交互来证明更高阶动态的复制.
主要成果:
- 双向相互作用的平稳态动态可以通过缩放的参数复制更高阶的模拟.
- 动态变化的疾病参数允许对联模型模拟过渡和稳定状态的高阶动态.
- 该近似对于模拟错误规范是可靠的,并且适用于复杂,异质的超图.
结论:
- 配对相互作用模型可以通过参数缩放来近似高阶传染动态.
- 高阶网络拓可以通过修改的低阶模型有效地表示.
- 超图形拓异质性可能会影响对近似的准确性.
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