Comprehensive analysis of disease dynamics using nonlinear fractional order SEIRS model with Crowley–Martin functional response and saturated treatment

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Bouissa Ayoub, Tsouli Najib
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引用次数: 0

Abstract

This paper presents a comprehensive study of disease spreading dynamics through the application of a nonlinear fractional order epidemic SEIRS model. By incorporating the Crowley–Martin type functional response and a saturated treatment function, the model effectively captures the intricacies of real-world epidemics. Our research establishes the existence, uniqueness, non-negativity and boundedness of the solution, while also investigating the model’s fundamental reproduction number. Additionally, we conduct a thorough analysis of the specific conditions governing the local and global stability of the model’s equilibriums. A notable observation is the variation of the reproduction number with the fractional-order α, which represents a memory effect on individuals’ dynamic behavior and reveals the influence of interactions between compartments. To validate these theoretical findings, we employ numerical simulations using Matlab, demonstrating that inhibition measures for susceptibles and the saturated treatment parameters play a pivotal role in determining the disease state. Specifically, we observe that as these parameter values increase, the transition from endemic equilibrium to disease-free equilibrium occurs.

利用非线性分数阶 SEIRS 模型与 Crowley-Martin 功能响应和饱和治疗对疾病动态进行综合分析
本文通过应用非线性分数阶流行病 SEIRS 模型,对疾病传播动态进行了全面研究。通过结合 Crowley-Martin 型功能响应和饱和治疗功能,该模型有效地捕捉了现实世界中错综复杂的流行病。我们的研究确定了解的存在性、唯一性、非负性和有界性,同时还研究了模型的基本繁殖数。此外,我们还对模型平衡的局部和全局稳定性的具体条件进行了深入分析。一个值得注意的观察结果是繁殖数随分数阶 α 的变化,这代表了个体动态行为的记忆效应,并揭示了隔室之间相互作用的影响。为了验证这些理论发现,我们使用 Matlab 进行了数值模拟,证明易感者的抑制量和饱和处理参数在决定疾病状态方面起着关键作用。具体来说,我们观察到,随着这些参数值的增加,会出现从地方病平衡到无病平衡的转变。
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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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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