高级时间延迟信息对多重网络中流行病传播的影响
Zehui Zhang1, Fang Wang1, Lilin Liu2
1Laboratory of Intelligent Computing and Information Processing of the Ministry of Education and National Centre for Applied Mathematics in Hunan, Xiangtan University, Xiangtan, 411105, China.
Infectious Disease Modelling
|December 10, 2025
概括
这项研究引入了一个新的流行病模型,考虑化期和复杂的社会相互作用. 这些发现突显了与化阶段同步的宣传活动如何能够缓解疾病传播.
科学领域:
- 流行病学 流行病学
- 网络科学 网络科学
- 数学建模的数学建模
背景情况:
- 传统的流行病模型往往简化了社会互动,忽视了疾病的潜伏期.
- 这些简化限制了现实世界传输动态预测的准确性.
研究的目的:
- 开发一种新的随机模型,整合高阶社会相互作用和疾病化期.
- 调查延迟意识的采用和化对流行病传播的综合影响.
主要方法:
- 构建了一个双层网络模型:一个用于信息传播的意识层和一个使用SIS模型的流行病层.
- 马尔科夫链分析被用来确定疫情值.
- 进行了数值模拟来评估流行病的结果.
主要成果:
- 高级延迟相互作用与双向相互作用相比,显著加快信息传播.
- 潜伏期增加了隐藏的传播风险,但也为传播意识提供了一个窗口.
- 意识扩散与化阶段的同步可以减轻疫情的爆发.
结论:
- 开发的模型为了解疾病传播提供了更现实的框架.
- 公共卫生干预必须考虑疾病的潜伏期,以实现有效的同步.
- 综合复杂的社会动态和化延迟对于准确的流行病预测至关重要.
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