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淋巴丝虫病传播的敏感性分析与参数估计

Sensitivity analysis and parameters estimation for the transmission of lymphatic filariasis.

作者信息

Stephano Mussa A, Mayengo Maranya M, Irunde Jacob I, Kuznetsov Dmitry

机构信息

School of Computation and Communication Science and Engineering, The Nelson Mandela African Institution of Science and Technology (NM-AIST), P.O.BOX 447 Arusha, Tanzania.

Mkwawa University College of Education, Department of Mathematics, Physics and Informatics, P.O.Box 2513, Iringa, Tanzania.

出版信息

Heliyon. 2023 Sep 17;9(9):e20066. doi: 10.1016/j.heliyon.2023.e20066. eCollection 2023 Sep.

Abstract

Lymphatic filariasis is a neglected tropical disease which poses public health concern and socio-economic challenges in developing and low-income countries. In this paper, we formulate a deterministic mathematical model for transmission dynamics of lymphatic filariasis to generate data by white noise and use least square method to estimate parameter values. The validity of estimated parameter values is tested by Gaussian distribution method. The residuals of model outputs are normally distributed and hence can be used to study the dynamics of Lymphatic filariasis. After deriving the basic reproduction number, by the next generation matrix approach, the Partial Rank Correlation Coefficient is employed to explore which parameters significantly affect and most influential to the model outputs. The analysis for equilibrium states shows that the Lymphatic free equilibrium is globally asymptotically stable when the basic reproduction number is less a unity and endemic equilibrium is globally asymptotically stable when . The findings reveal that rate of human infection, recruitment rate of mosquitoes increase the average new infections for Lymphatic filariasis. Moreover, asymptomatic individuals contribute significantly in the transmission of Lymphatic filariasis.

摘要

淋巴丝虫病是一种被忽视的热带疾病,在发展中国家和低收入国家引发了公共卫生问题和社会经济挑战。在本文中,我们构建了一个用于淋巴丝虫病传播动力学的确定性数学模型,通过白噪声生成数据,并使用最小二乘法估计参数值。采用高斯分布方法检验估计参数值的有效性。模型输出的残差呈正态分布,因此可用于研究淋巴丝虫病的动态变化。通过下一代矩阵方法推导出基本再生数后,利用偏秩相关系数来探究哪些参数对模型输出有显著影响且最具影响力。对平衡态的分析表明,当基本再生数小于1时,无淋巴丝虫病平衡态全局渐近稳定;当基本再生数大于1时,地方病平衡态全局渐近稳定。研究结果表明,人类感染率、蚊子招募率增加了淋巴丝虫病的平均新感染数。此外,无症状个体在淋巴丝虫病传播中起重要作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e08/10559806/0284fe8dff43/gr001.jpg

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