易受感染-恢复-易受感染的过程与简单复合体竞争
Lina Zhao1, Haiying Wang1, Huijie Yang1
1University of Shanghai for Science and Technology, Business School, 334 Jungong Road, Shanghai 200093, People's Republic of China.
Physical review. E
|February 7, 2025
概括
这项研究引入了竞争性传染的新模型,考虑了复杂的相互作用. 该模型揭示了临界质量效应和多样化的结果,改善了我们对疾病传播动态的理解.
科学领域:
- 流行病学 流行病学
- 复杂系统科学 复杂系统科学
- 数学建模的数学建模
背景情况:
- 传染物与其他传播量相互作用,而不是孤立地.
- 在现实世界系统中,高阶交互很普遍.
- 易感-感染-康复-易感 (SIRS) 模型对于理解疾病动态至关重要.
研究的目的:
- 为在简化复合体中竞争SIRS过程提出一个新的随机模型.
- 开发和分析模型的决定性微观马尔科夫链 (MMC) 和平均场 (MF) 版本.
- 调查感染持久性的条件,并探索新出现的现象.
主要方法:
- 在简化复合体上对竞争SIRS过程开发一个随机模型.
- 从随机框架中衍生出的决定性MMC和MF模型的制定.
- 对模型动态的分析,包括稳定状态和振荡.
- 数字模拟用于验证分析预测和发现新出现的行为.
主要成果:
- 随机模型表现出八个不同的类别的依赖初始条件.
- MMC模型复制了所有八个类别,而MF模型捕获了七个.
- 在MMC和随机模型中观察到一个具有三个稳定状态的独特类,但MF错过了它.
- 在没有高阶相互作用的情况下,MF模型显示了一个额外的类,具有无限的稳定状态.
- 两种MMC和MF模型都表现出持续的振荡,其中一种传染物消失,另一种传染物达到极限周期.
- 观察到临界质量效应,不连续的相位过渡和双稳定性.
结论:
- 拟议的模型准确地捕捉了复杂的传染动态,包括更高层次的相互作用.
- 随机,MMC和MF模型之间的差异凸显了相互作用复杂性的重要性.
- 这些模型提供了对竞争性传染病的临界质量,相位过渡和多稳定性的洞察.
- 这项研究促进了对复杂网络结构中的流行病建模的理解.
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