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登革热的数学建模与动态分析:考察经济和心理影响并预测到2030年的疾病趋势——以尼泊尔为例

Mathematical modeling and dynamic analysis of dengue fever: examining economic and psychological impacts and forecasting disease trends through 2030-a case study of Nepal.

作者信息

Gholami Hossein, Gachpazan Mortaza, Erfanian Majid

机构信息

Department of Applied Mathematics, Ferdowsi University of Mashhad, Mashhad, Iran.

Department of Science, School of Mathematical Sciences, University of Zabol, Zabol, Iran.

出版信息

Sci Rep. 2025 Mar 23;15(1):10027. doi: 10.1038/s41598-025-94527-8.

DOI:10.1038/s41598-025-94527-8
PMID:40122899
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11931001/
Abstract

Dengue fever is a viral disease predominantly found in tropical and subtropical regions. The mild form presents with fever and flu-like symptoms, whereas the severe form can cause significant bleeding, a drastic drop in blood pressure, and even death. A mathematical model was developed consisting of ten classes: seven for humans and three for mosquitoes. The model was then reduced to eight classes to better simulate the transmission dynamics of the dengue virus. In numerical experiments, it was fitted to dengue infection data from 2022 and from 2004 to 2022 in Nepal using the least squares method. Sensitivity analysis identified the parameters with the most significant influence on the basic reproduction number. Conclusions The model has been validated to ensure the positivity and boundedness of solutions. The basic reproduction number ([Formula: see text]) was derived using the next-generation matrix approach. We have analytically and graphically demonstrated that both the Dengue-free and endemic equilibrium points are locally and globally stable. Additionally, the presence of a forward bifurcation was confirmed through the Center Manifold theory. Sensitivity analysis identified the parameters with the most significant influence on the basic reproduction number. Finally, the model equations were numerically solved using the Runge-Kutta (ODE45) method to assess the impact of key parameters on the system's behavior. Moreover, we analyzed the economic and psychological effects of dengue fever on hospitalized patients in Nepal from 2004 to 2022 and projected the disease trend through 2030. Furthermore, this study was compared with the three other articles in terms of methodology and model design.

摘要

登革热是一种主要在热带和亚热带地区发现的病毒性疾病。轻症表现为发热和流感样症状,而重症可导致严重出血、血压急剧下降甚至死亡。开发了一个由十个类别组成的数学模型:七个针对人类,三个针对蚊子。然后将该模型简化为八个类别,以更好地模拟登革热病毒的传播动态。在数值实验中,使用最小二乘法将其拟合到尼泊尔2022年以及2004年至2022年的登革热感染数据。敏感性分析确定了对基本再生数影响最显著的参数。结论该模型已经过验证,以确保解的正性和有界性。使用下一代矩阵方法推导出基本再生数([公式:见正文])。我们已经通过分析和图形证明,无登革热平衡点和地方病平衡点在局部和全局都是稳定的。此外,通过中心流形理论证实了正向分岔的存在。敏感性分析确定了对基本再生数影响最显著的参数。最后,使用龙格 - 库塔(ODE45)方法对模型方程进行数值求解,以评估关键参数对系统行为的影响。此外,我们分析了2004年至2022年登革热对尼泊尔住院患者的经济和心理影响,并预测了到2030年的疾病趋势。此外,本研究在方法和模型设计方面与其他三篇文章进行了比较。

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2
The stability analysis of a nonlinear mathematical model for typhoid fever disease.伤寒病的一个非线性数学模型的稳定性分析。
Sci Rep. 2023 Sep 15;13(1):15284. doi: 10.1038/s41598-023-42244-5.
3
Mathematical assessment of monkeypox disease with the impact of vaccination using a fractional epidemiological modeling approach.
用分数流行病学建模方法评估接种疫苗对猴痘疾病的影响的数学评估。
Sci Rep. 2023 Aug 20;13(1):13550. doi: 10.1038/s41598-023-40745-x.
4
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Front Public Health. 2023 Feb 17;11:1101436. doi: 10.3389/fpubh.2023.1101436. eCollection 2023.
5
A Systematic Review of Mathematical Models of Dengue Transmission and Vector Control: 2010-2020.基于数学模型的登革热传播与病媒控制的系统评价:2010-2020 年。
Viruses. 2023 Jan 16;15(1):254. doi: 10.3390/v15010254.
6
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7
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8
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9
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PLoS Med. 2016 Nov 29;13(11):e1002181. doi: 10.1371/journal.pmed.1002181. eCollection 2016 Nov.