用随机微分方程模拟霍乱流行病学

W. Iddrisu, Inusah D. Iddrisu, Abdul-Karim Iddrisu
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引用次数: 0

摘要

在本研究中,我们将codecadeo经典的SI-B流行病和地方病模型从确定性框架扩展到随机框架。然后,我们将其表述为在水生环境作用下感染个体数I t的随机微分方程。并证明了该随机微分方程的存在性和唯一性。推导了确定性模型的繁殖数r0,并研究了解的正性和不变区、两个平衡点(无病平衡点和地方病平衡点)和稳定性等定性特征,以确保模型的生物学意义。采用Euler-Maruyama数值方法对随机微分方程(SDE)模型进行了数值模拟。用该方法模拟感染个体数I t的SI-B随机微分方程的样本路径;结果表明,感染个体数随机微分方程的样本路径或轨迹是连续的但不可微的,感染个体数的SI-B随机微分方程模型在SI-B常微分方程模型的解内波动。我们提出的SDE模型的另一个重要特征是它的简单性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling Cholera Epidemiology Using Stochastic Differential Equations
In this study, we extend Codeço’s classical SI-B epidemic and endemic model from a deterministic framework into a stochastic framework. Then, we formulated it as a stochastic differential equation for the number of infectious individuals I t under the role of the aquatic environment. We also proved that this stochastic differential equation (SDE) exists and is unique. The reproduction number, R 0 , was derived for the deterministic model, and qualitative features such as the positivity and invariant region of the solution, the two equilibrium points (disease-free and endemic equilibrium), and stabilities were studied to ensure the biological meaningfulness of the model. Numerical simulations were also carried out for the stochastic differential equation (SDE) model by utilizing the Euler-Maruyama numerical method. The method was used to simulate the sample path of the SI-B stochastic differential equation for the number of infectious individuals I t , and the findings showed that the sample path or trajectory of the stochastic differential equation for the number of infectious individuals I t is continuous but not differentiable and that the SI-B stochastic differential equation model for the number of infectious individuals I t fluctuates inside the solution of the SI-B ordinary differential equation model. Another significant feature of our proposed SDE model is its simplicity.
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