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Chaos in a seasonally perturbed SIR model: avian influenza in a seabird colony as a paradigm

机译:季节性扰动SIR模型中的混乱:以海鸟殖民地中的禽流感为例

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摘要

Seasonality is a complex force in nature that affects multiple processes in wild animal populations. In particular, seasonal variations in demographic processes may considerably affect the persistence of a pathogen in these populations. Furthermore, it has been long observed in computer simulations that under seasonal perturbations, a host–pathogen system can exhibit complex dynamics, including the transition to chaos, as the magnitude of the seasonal perturbation increases. In this paper, we develop a seasonally perturbed Susceptible-Infected-Recovered model of avian influenza in a seabird colony. Numerical simulations of the model give rise to chaotic recurrent epidemics for parameters that reflect the ecology of avian influenza in a seabird population, thereby providing a case study for chaos in a host– pathogen system. We give a computer-assisted exposition of the existence of chaos in the model using methods that are based on the concept of topological hyperbolicity. Our approach elucidates the geometry of the chaos in the phase space of the model, thereby offering a mechanism for the persistence of the infection. Finally, the methods described in this paper may be immediately extended to other infections and hosts, including humans.
机译:季节性是自然界中的一种复杂力量,会影响野生动物种群的多个过程。特别是,人口统计过程中的季节性变化可能会大大影响这些人群中病原体的持久性。此外,长期以来在计算机模拟中已经观察到,在季节扰动下,宿主-病原体系统会表现出复杂的动力学,包括随着季节扰动幅度的增加而向混沌的过渡。在本文中,我们建立了一个季节性扰动的海鸟群落中禽流感的易感感染恢复模型。该模型的数值模拟导致了反映参数的混沌性反复流行,这些参数反映了海鸟种群中禽流感的生态,从而为宿主-病原体系统的混乱提供了案例研究。我们使用基于拓扑双曲概念的方法,对模型中混沌的存在进行了计算机辅助的阐述。我们的方法阐明了模型相空间中的混沌几何形状,从而为感染的持久性提供了一种机制。最后,本文描述的方法可能会立即扩展到其他感染和宿主,包括人类。

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