On the global stability of the discrete-time epidemic models: A new approach.

IF 2.6 4区 工程技术 Q1 Mathematics
Omaima Slimani, Bouchra Aylaj, Saber Elaydi
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引用次数: 0

Abstract

We developed a unified analytical framework for the global dynamics of discrete-time susceptible infectious susceptible (SIS) epidemic models with nonlinear recruitment. Emphasis was placed on demographic feedback through Beverton-Holt and Ricker-type recruitment, which regulates host population size and thereby shapes transmission and long-term persistence (Persistence allows population densities to approach zero asymptotically, wheras uniform persistence requires them to remain bounded away from zero). Under minimal assumptions, we reduced non-autonomous systems to appropriately defined autonomous limiting systems and used this reduction to obtain a complete global threshold characterization: When the basic reproduction number $ R_{0} > 1 $, the endemic equilibrium existed and was globally asymptotically stable; when $ R_{0}\le 1 $, solutions converged to the disease-free state. The approach extended to periodically forced SIS models, which showed that the threshold and stability conclusions persisted in the periodic non-autonomous setting. The results unified and strengthened prior work and clarify how recruitment dynamics govern persistence in discrete-time epidemic systems.

离散时间流行病模型的全局稳定性:一种新方法。
我们开发了一个具有非线性招募的离散时间易感感染易感(SIS)流行病模型的全球动力学统一分析框架。重点放在通过贝弗顿-霍尔特和里克型招募的人口反馈上,这调节了宿主人口规模,从而形成了传播和长期持久性(持久性允许人口密度逐渐接近零,而均匀持久性要求它们保持在零附近)。在最小假设条件下,我们将非自治系统约简为适当定义的自治极限系统,并利用这一约简得到了完整的全局阈值表征:当基本繁殖数$ R_{0} > 1 $时,存在地方性平衡,且全局渐近稳定;当$ R_{0}\le 1 $时,解收敛于无病状态。该方法扩展到周期性强迫SIS模型,结果表明阈值和稳定性结论在周期性非自治设置下仍然存在。结果统一和加强了先前的工作,并阐明了招募动态如何控制离散时间流行病系统的持久性。
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
Mathematical Biosciences and Engineering
Mathematical Biosciences and Engineering 工程技术-数学跨学科应用
CiteScore
3.90
自引率
7.70%
发文量
586
审稿时长
>12 weeks
期刊介绍: Mathematical Biosciences and Engineering (MBE) is an interdisciplinary Open Access journal promoting cutting-edge research, technology transfer and knowledge translation about complex data and information processing. MBE publishes Research articles (long and original research); Communications (short and novel research); Expository papers; Technology Transfer and Knowledge Translation reports (description of new technologies and products); Announcements and Industrial Progress and News (announcements and even advertisement, including major conferences).
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