Treatment of Polio Delayed Epidemic Model via Computer Simulations

IF 2 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Muhammad Naveed, D. Baleanu, A. Raza, M. Rafiq, Atif Hassan Soori
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引用次数: 1

Abstract

: Through the study, the nonlinear delayed modelling has vital sig-nificance in the different field of allied sciences like computational biology, computational chemistry, computational physics, computational economics and many more. Polio is a contagious viral illness that in its most severe form causes nerve injury leading to paralysis, difficulty breathing and sometimes death. In recent years, developing regions like Asia, Africa and sub-continents facing a dreadful situation of poliovirus. That is the reason we focus on the treatment of the polio epidemic model with different delay strategies in this article. Polio delayed epidemic model is categorized into four compartments like susceptible, exposed, infective and vaccinated classes. The equilibria, positivity, boundedness, and reproduction number are investigated. Also, the sensitivity of the parameters is analyzed. Well, known results like the Routh Hurwitz criterion and Lyapunov function stabilities are investigated for polio delayed epidemic model in the sense of local and global respectively. Further-more, the computer simulations are presented with different traditions in the support of the analytical analysis of the polio delayed epidemic model.
脊髓灰质炎延迟流行模型的计算机模拟治疗
通过研究,非线性延迟建模在计算生物学、计算化学、计算物理、计算经济学等相关科学的不同领域具有重要意义。脊髓灰质炎是一种传染性病毒疾病,最严重的形式会导致神经损伤,导致瘫痪、呼吸困难,有时甚至死亡。近年来,亚洲、非洲和各次大陆等发展中区域面临着可怕的脊髓灰质炎病毒形势。这就是为什么我们在本文中重点讨论用不同的延迟策略治疗脊髓灰质炎流行模型的原因。脊髓灰质炎延迟流行模型分为易感、暴露、感染和接种四类。研究了系统的均衡性、正性、有界性和繁殖数。并对参数的灵敏度进行了分析。已知的结果如Routh Hurwitz准则和Lyapunov函数稳定性分别在局部和全局意义上对脊髓灰质炎延迟流行模型进行了研究。此外,还提出了不同传统的计算机模拟,以支持脊髓灰质炎延迟流行模型的分析分析。
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
Cmc-computers Materials & Continua
Cmc-computers Materials & Continua 工程技术-材料科学:综合
CiteScore
5.30
自引率
19.40%
发文量
345
审稿时长
1 months
期刊介绍: This journal publishes original research papers in the areas of computer networks, artificial intelligence, big data management, software engineering, multimedia, cyber security, internet of things, materials genome, integrated materials science, data analysis, modeling, and engineering of designing and manufacturing of modern functional and multifunctional materials. Novel high performance computing methods, big data analysis, and artificial intelligence that advance material technologies are especially welcome.
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