流行病值和SIS模型在指向复杂网络上的本地化
Vinícius B Müller1, Fernando L Metz1
1Federal University of Rio Grande do Sul, Physics Institute, 91501-970 Porto Alegre, Brazil.
Physical review. E
|January 21, 2026
概括
本研究使用易受感染易受感染 (SIS) 模型分析了在定向网络上传播的流行病. 我们发现网络结构会影响疾病的传播,可能会将流行病局部化到特定的节点上.
科学领域:
- 流行病学 流行病学
- 网络科学 网络科学
- 统计物理 统计物理
背景情况:
- 易感-感染-易感 (SIS) 模型对于理解流行病动态至关重要.
- 复杂的网络,特别是有针对性的网络,显著影响疾病传播模式.
- 化平均场近似为分析这些复杂系统提供了一种可处理的方法.
研究的目的:
- 在指向复杂网络上研究易受感染易受感染 (SIS) 模型.
- 导出相位图并确定不平衡相位过渡的条件.
- 描述网络异质性对流行病传播的影响.
主要方法:
- 使用灭的平均场近似.
- 应用随机矩阵理论来分析固定点感染概率.
- 导出相位图和临界线.
主要成果:
- 在c≥λ^{-1}的吸收和特有阶段之间发生不平衡阶段过渡.
- 证明了临界线与度分布的独立性,但对感染率分布的敏感性.
- 在流行病值附近的逆参与率的分歧表明潜在的疾病局部化.
结论:
- 网络异质性系统地塑造了在定向网络上传播的流行病.
- 这些发现提供了关于疾病局部化和传播动态的见解.
- 该研究为分析复杂网络上的流行病模型提供了一个强大的框架.
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