通过SIR、SEIR和BSEIR数学模型分析土耳其结核病

IF 1.8 4区数学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Mathematical and Computer Modelling of Dynamical Systems Pub Date : 2021-01-02 DOI:10.1080/13873954.2021.1881560

Yasin Ucakan, S. Gulen, K. Koklu

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引用次数: 10

摘要

由于数学模型在研究传染病动力学中起着关键作用，因此开发了许多传染病的数学模型。在这篇论文中，它的目的是确定土耳其结核病(TB)的动态，它将在多大程度上影响未来以及疫苗治疗对该疾病的影响。为此，文献中的三种数学模型(SIR, SEIR和BSEIR)被认为是针对土耳其的情况。利用2005 - 2015年TB报告数据，采用最小二乘法得到模型参数。结果表明，三种模型的基本繁殖比均小于1。此外，还对模型的稳定性分析和模型参数的敏感性分析进行了讨论。最后，比较了三种模型结果的准确性，并讨论了疫苗接种率的影响。

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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Analysing of Tuberculosis in Turkey through SIR, SEIR and BSEIR Mathematical Models

ABSTRACT Since mathematical models play a key role in investigating the dynamics of infectious diseases, many mathematical models for these diseases are developed. In this paper, it is aimed to determine the dynamics of Tuberculosis (TB) in Turkey, how much it will affect the future and the impact of vaccine therapy on the disease. For this purpose, three mathematical models (SIR, SEIR and BSEIR) in the literature are considered for the case of Turkey. The model parameters are obtained with TB reported data from 2005 to 2015 by using the least square method. The obtained results revealed that the basic reproduction ratio for all three models is less than 1. Moreover, the stability analysis of the models and sensitivity analysis of the model parameters are presented and discussed. Finally, the accuracy of results for all three models is compared and the effect of the vaccination rate is discussed.

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来源期刊

Mathematical and Computer Modelling of Dynamical Systems 数学-计算机：跨学科应用

CiteScore

3.80

自引率

5.30%

发文量

审稿时长

>12 weeks

期刊介绍： Mathematical and Computer Modelling of Dynamical Systems (MCMDS) publishes high quality international research that presents new ideas and approaches in the derivation, simplification, and validation of models and sub-models of relevance to complex (real-world) dynamical systems. The journal brings together engineers and scientists working in different areas of application and/or theory where researchers can learn about recent developments across engineering, environmental systems, and biotechnology amongst other fields. As MCMDS covers a wide range of application areas, papers aim to be accessible to readers who are not necessarily experts in the specific area of application. MCMDS welcomes original articles on a range of topics including: -methods of modelling and simulation- automation of modelling- qualitative and modular modelling- data-based and learning-based modelling- uncertainties and the effects of modelling errors on system performance- application of modelling to complex real-world systems.