具有一般感染形式和Ornstein-Uhlenbeck过程的随机HTLV-I感染模型的动力学行为

IF 5.6 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Zhenfeng Shi , Daqing Jiang
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引用次数: 14

摘要

本研究考虑Ornstein-Uhlenbeck过程对感染率的扰动,建立了具有一般感染形态的HTLV-I感染模型。通过构造几个合适的Lyapunov函数和一个紧集,利用强数定律和Fatou引理,得到了随机模型遍历平稳分布η(⋅)存在唯一性的充分条件。从生物学意义上讲,这意味着HTLV-I感染的长期持续性。此外,通过Itô的积分随机模型转化为相应的线性化系统。然后通过求解Fokker-Planck方程,得到了随机模型准平衡态周围概率密度函数的精确表达式。此外,还建立了HTLV-I感染消灭的充分条件。最后,考虑不同的发生率函数,我们采用数值模拟来支持我们的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamical behaviors of a stochastic HTLV-I infection model with general infection form and Ornstein–Uhlenbeck process

In this study, considering the Ornstein–Uhlenbeck process to perturb the infection rate, we develop a HTLV-I infection model with general infection form. By constructing several suitable Lyapunov functions and a compact set, and then using the strong law of numbers and Fatou’s lemma, we obtain sufficient conditions for the existence and uniqueness of the ergodic stationary distribution η() for the stochastic model. This implies long-term persistence of HTLV-I infection in a biological sense. Moreover, by using Itô’s integral stochastic model is transformed into the corresponding linearized system. Then solving the Fokker–Planck equation, we obtain the exact expression of probability density function around the quasi-equilibrium of the stochastic model. In addition, sufficient conditions for the extinction of HTLV-I infection are established. Finally, considering different incidence rate functions, we employ numerical simulations to support our results.

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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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