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Phase-adjusted estimation of the number of Coronavirus Disease 2019 cases in Wuhan, China.中国武汉2019冠状病毒病病例数的相位调整估计。
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具有感染个体时间延迟的分数阶流行病模型的稳定性分析与霍普夫分岔

Stability analysis and Hopf bifurcation in fractional order epidemic model with a time delay in infected individuals.

作者信息

Mahata Animesh, Paul Subrata, Mukherjee Supriya, Roy Banamali

机构信息

Mahadevnagar High School, Maheshtala, Kolkata 700141, West Bengal, India.

Department of Mathematics, Arambagh Government Polytechnic, Arambagh, West Bengal, India.

出版信息

Partial Differ Equ Appl Math. 2022 Jun;5:100282. doi: 10.1016/j.padiff.2022.100282. Epub 2022 Feb 2.

DOI:10.1016/j.padiff.2022.100282
PMID:37521808
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8809664/
Abstract

Infectious diseases have been a constant cause of disaster in human population. Simultaneously, it provides motivation for math and biology professionals to research and analyze the systems that drive such illnesses in order to predict their long-term spread and management. During the spread of such diseases several kinds of delay come into play, owing to changes in their dynamics. Here, we have studied a fractional order dynamical system of susceptible, exposed, infected, recovered and vaccinated population with a single delay incorporated in the infectious population accounting for the time period required by the said population to recover. We have employed Adam-Bashforth-Moulton technique for deriving numerical solutions to the model system. The stability of all equilibrium points has been analyzed with respect to the delay parameter. Utilizing actual data from India COVID-19 instances, the parameters of the fractional order SEIRV model were calculated. Graphical demonstration and numerical simulations have been done with the help of MATLAB (2018a). Threshold values of the time delay parameter have been found beyond which the system exhibits Hopf bifurcation and the solutions are no longer periodic.

摘要

传染病一直是人类灾难的一个持续根源。同时,它也促使数学和生物学专业人员研究和分析导致此类疾病的系统,以便预测其长期传播和管控情况。在这类疾病的传播过程中,由于其动态变化会出现几种延迟情况。在此,我们研究了一个包含易感、潜伏、感染、康复和接种人群的分数阶动力系统,在感染人群中纳入了单一延迟,以考虑该人群康复所需的时间段。我们采用亚当 - 巴斯福思 - 莫尔顿技术来推导该模型系统的数值解。针对延迟参数分析了所有平衡点的稳定性。利用印度新冠肺炎病例的实际数据,计算了分数阶SEIRV模型的参数。借助MATLAB(2018a)进行了图形演示和数值模拟。已找到时间延迟参数的阈值,超过该阈值系统会出现霍普夫分岔,且解不再是周期性的。