Sustained oscillatory mosquito population suppression analysis based on a hybrid switching dynamical system model.

IF 2.7 4区 数学 Q2 BIOLOGY
Yufeng Wang, Yining Chen, Jia Li, Jianshe Yu
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引用次数: 0

Abstract

In this paper, we develop a hybrid dynamical system to model mosquito population suppression incorporating both time and state-dependent switching. The time-dependent switching arises from a mismatch between the sexual lifespan of sterile mosquitoes and the sampling period, while the state-dependent switching is governed by the relation between the state of wild mosquitoes at sampling instants and the epidemiological threshold. We investigate the long-term dynamics of the hybrid system with sampling period exceeding the sexual lifespan. The wild population is shown to converge to a pseudo-equilibrium when the epidemiological threshold exceeds this equilibrium value. For the other situation, we establish sufficient conditions for the existence of a unique (pseudo)-harmonic solution and analyze its stability. Using Poincaré mapping, we further derive explicit existence criteria for subharmonic solutions and rigorously prove their global asymptotic stability. Finally, some numerical examples are provided to illustrate our theoretical findings and to deliver practical insights for release strategy development.

基于混合开关动力系统模型的持续振荡蚊子种群抑制分析。
在本文中,我们开发了一个混合动力系统来模拟蚊子种群抑制,同时考虑了时间和状态依赖开关。时间依赖性转换是由于不育蚊的性寿命与采样周期不匹配造成的,状态依赖性转换是由野生蚊在采样时刻的状态与流行病学阈值之间的关系决定的。我们研究了采样周期超过性寿命的杂交系统的长期动力学。当流行病学阈值超过这个平衡值时,野生种群收敛到一个伪平衡。对于另一种情况,我们建立了唯一(伪)调和解存在的充分条件,并分析了其稳定性。利用poincarcarr映射,进一步导出了次调和解的显式存在准则,并严格证明了其全局渐近稳定性。最后,提供了一些数值例子来说明我们的理论发现,并为发布策略开发提供实际的见解。
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
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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