具有对数 Ornstein-Uhlenbeck 过程的随机玉米条纹病毒流行模型的动态分析。

IF 2.2 4区 数学 Q2 BIOLOGY Journal of Mathematical Biology Pub Date : 2024-07-17 DOI:10.1007/s00285-024-02127-3
Qun Liu
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引用次数: 0

摘要

为了描述玉米条纹病毒感染的传播动态,本文首先建立了一个随机玉米条纹病毒感染模型,其中随机波动由对数奥恩斯坦-乌伦贝克过程来描述。无论从生物学意义还是数学角度来看,这种方法都能合理地模拟主要参数的随机影响。然后,我们研究了随机系统的详细动态,包括全局解的存在性和唯一性、静态分布的存在性、感染玉米和感染叶蝉载体的指数消亡。特别是,通过求解随机系统对应的五维代数方程,我们得到了随机系统准流行平衡附近概率密度函数的具体表达式,为静态分布提供了有价值的启示。最后,我们使用 Milstein 高阶数值方法对模型进行离散化处理,以数值说明我们的理论结果。我们的发现为更好地预防此类病毒的传播提供了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Dynamical analysis of a stochastic maize streak virus epidemic model with logarithmic Ornstein-Uhlenbeck process.

To describe the transmission dynamics of maize streak virus infection, in the paper, we first formulate a stochastic maize streak virus infection model, in which the stochastic fluctuations are depicted by a logarithmic Ornstein-Uhlenbeck process. This approach is reasonable to simulate the random impacts of main parameters both from the biological significance and the mathematical perspective. Then we investigate the detailed dynamics of the stochastic system, including the existence and uniqueness of the global solution, the existence of a stationary distribution, the exponential extinction of the infected maize and infected leafhopper vector. Especially, by solving the five-dimensional algebraic equations corresponding to the stochastic system, we obtain the specific expression of the probability density function near the quasi-endemic equilibrium of the stochastic system, which provides valuable insights into the stationary distribution. Finally, the model is discretized using the Milstein higher-order numerical method to illustrate our theoretical results numerically. Our findings provide a groundwork for better methods of preventing the spread of this type of virus.

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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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