沃尔巴克氏体感染雄蚊非自主延迟种群抑制模型的动力学研究。

IF 1.8 4区 数学 Q3 ECOLOGY
Journal of Biological Dynamics Pub Date : 2024-12-01 Epub Date: 2024-12-04 DOI:10.1080/17513758.2024.2437034
Yufeng Wang, Jianshe Yu
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引用次数: 0

摘要

本文建立了蚊子种群抑制的非自治时滞微分方程模型。在建立了解的正性和有界性之后,我们研究了感染沃尔巴克氏体或不感染沃尔巴克氏体的雄蚊模型的动力学行为。更具体地说,对于不感染雄蚊的模型,我们分析了平衡点的渐近稳定性,并证明了模型在一定条件下发生Hopf分岔。对于包含受感染雄蚊的模型,我们得到了原点全局渐近稳定的充分条件。数值例子说明和支持我们的理论发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamics of a non-autonomous delay mosquito population suppression model with Wolbachia-infected male mosquitoes.

In this paper, we develop a non-autonomous delay differential equation model for mosquito population suppression. After establishing the positiveness and boundedness of the solutions, we study the dynamical behaviours of the model with or without Wolbachia-infected male mosquitoes. More specifically, for the model without infected male mosquitoes, we analyse the asymptotic stability of the equilibria and demonstrate that the model undergo Hopf bifurcations under certain conditions. For the model incorporating infected male mosquitoes, we derive sufficient conditions for the global asymptotic stability of the origin. Numerical examples are provided to illustrate and support our theoretical findings.

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来源期刊
Journal of Biological Dynamics
Journal of Biological Dynamics ECOLOGY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
4.90
自引率
3.60%
发文量
28
审稿时长
33 weeks
期刊介绍: Journal of Biological Dynamics, an open access journal, publishes state of the art papers dealing with the analysis of dynamic models that arise from biological processes. The Journal focuses on dynamic phenomena at scales ranging from the level of individual organisms to that of populations, communities, and ecosystems in the fields of ecology and evolutionary biology, population dynamics, epidemiology, immunology, neuroscience, environmental science, and animal behavior. Papers in other areas are acceptable at the editors’ discretion. In addition to papers that analyze original mathematical models and develop new theories and analytic methods, the Journal welcomes papers that connect mathematical modeling and analysis to experimental and observational data. The Journal also publishes short notes, expository and review articles, book reviews and a section on open problems.
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