基于恐惧致死意识的流行病模型建模和分析。

IF 1.8 4区 数学 Q3 ECOLOGY
Journal of Biological Dynamics Pub Date : 2025-12-01 Epub Date: 2025-01-29 DOI:10.1080/17513758.2025.2458890
Ling Xue, Junqi Huo, Yuxin Zhang
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引用次数: 0

摘要

在本文中,我们建立了一个室室模型,其中传播率与对COVID-19感染的恐惧相关。我们给出了流行病模型的详细分析,并建立了一个正不变集存在的结果。对基本繁殖数R0的表达式进行了表征。结果表明,当R01时,系统的无病平衡点(DFE)是全局渐近稳定的;当R0=1时,系统呈现正向分岔。当R0>1时,系统是一致持久的,DFE是不稳定的,存在一个唯一的全局渐近稳定的地方性平衡(EE)。我们利用加拿大2021年9月1日至10月10日的报告数据拟合未知参数,并进行敏感性分析。带意识模型的定量分析表明了降低传播率、增强公众防护意识的意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling and analysis of an epidemic model with awareness caused by deaths due to fear.

In this paper, we establish a compartmental model in which the transmission rate is associated with the fear of being infected by COVID-19. We provide a detailed analysis of the epidemic model and established results for the existence of a positively invariant set. The expression of the basic reproduction number R0 is characterized. It is shown that the disease-free equilibrium (DFE) is globally asymptotically stable if R0<1, and the system exhibits a forward bifurcation if R0=1. When R0>1, the system is uniformly persistent, the DFE is unstable and there exists a unique and globally asymptotic stable endemic equilibrium (EE). We fit unknown parameters using the reported data in Canada from September 1 to October 10, 2021, and carry out sensitivity analysis. The quantitative analysis of the model with awareness demonstrates the significance of reducing the transmission rate and enhancing public protective awareness.

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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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