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Modeling of epidemic spreading with white Gaussian noise
  • 时间：0
  • 分类：O175.1[理学—数学;理学—基础数学] TN92[电子电信—通信与信息系统;电子电信—信息与通信工程]
  • 作者机构：[1]Max-Planck-Institutefor Mathematics in the Sciences, Leipzig 04103, Germany, [2]College of Physical Science and Technology, Central China Normal University, Wuhan 430079, China, [3]Complexity Science Center, Institute of Particle Physics, Central China Normal University, Wuhan 430079, China
  • 相关基金：supported in part by the National Natural Science Foundation of China （10647125, 10635020, 10975057, 10975062）; the Programme of Introducing Tal-ents of Discipline to Universities （B08033）
作者： GU Jiao[1], GAO ZongMao[2], Li Wei[1,3]
关键词： 流行病模型, 高斯白噪声, 噪声传播, SIR模型, 模型预测, 变异系数, 仿真模型, 仿真结果, epidemic process, SIR model, white noise, variant coefficients
中文摘要：

由需要激发了在流行传播的预言包括个人和抑制效果的不同特征，我们基于传统的先生模型与变体系数和白 Gaussian 噪音造一个模型。分析并且模型预言的模拟结果被介绍并且讨论。模拟在易受影响的个人的一个更高的百分比和移开的个人的一个更低的百分比用变体系数结果显示出那。当噪音在模型被包括时，感染的个人的百分比比用传统的先生预言了那让一座更宽的山峰和更多的变化当模特儿。

英文摘要：

Motivated by the need to include the different characteristics of individuals and the damping effect in predictions of epidemic spreading, we build a model with variant coefficients and white Gaussian noise based on the traditional SIR model. The analytic and simulation results predicted by the model are presented and discussed. The simulations show that using the variant coefficients results in a higher percentage of susceptible individuals and a lower percentage of removed individuals. When the noise is included in the model, the percentage of infected individuals has a wider peak and more fluctuations than that predicted using the traditional SIR model.

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