埃塞俄比亚新型冠状病毒大流行双剂量疫苗模型与最优控制分析

F. Legesse, Koya Purnachandra Rao, T. Keno
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引用次数: 1

摘要

这种新型冠状病毒是最近发现的最大的病毒家族之一的成员,其症状从简单的感冒到极度的呼吸疼痛。在本文中,我们制定了一个确定性数学模型来估计COVID-19的传播动力学,其中包括(i)双剂量疫苗接种、(ii)预防和(iii)治疗等控制策略。此外,我们没有将所有感染人群视为一个整体,而是将其分为有症状和无症状人群,并分析其影响。这种分离是有意义的,因为各种报告表明,无症状病例比有症状病例更容易传播疾病。在适当的初始条件下,通过显示解的正性和有界性,证明了该模型具有良好的数学定态性和生物学意义。对于再现数,构造了参数公式,并根据埃塞俄比亚报告的实际数据计算了相关数值。此外,确定了无病平衡点和地方性平衡点,并利用Lyapunov函数技术讨论了它们的局部稳定性和全局稳定性。当R为0时,这些平衡点分别是局部渐近稳定的。在模型拟合和参数值估计之后,进行灵敏度分析,分析各参数对传动动力学的影响。换句话说,本研究可用于评估主要模型参数如何影响传动动力学和控制。利用庞特里亚金最大原则,实施最佳控制措施,目的是降低与感染、预防和治疗相关的负担。为了理解和可视化控制技术对疾病发展的影响,并说明本研究中产生的分析结果,进行了数值模拟研究。最后,研究结果表明,坚持所有的控制策略对最大限度地减少疾病在社会中的传播有很大的影响。这意味着,如果有关机构妥善管理控制战略,那么埃塞俄比亚人口中的疾病负担就会迅速减轻。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling and Optimal Control Analysis Applied to Real Cases of COVID-19 Pandemic with Double Dose Vaccination in Ethiopia
The novel coronavirus is a recently discovered member of one of the largest families of viruses with symptoms ranging from a simple cold to excruciating respiratory agony. In the present paper, a deterministic mathematical model is formulated to estimate the transmission dynamics of COVID-19 with the inclusion of control strategies like (i) double-dose vaccination, (ii) prevention, and (iii) treatment. In addition, instead of considering all infectious humans as one unit, we separate them into symptomatic and asymptomatic groups, and the impact is analyzed. This separation is meaningful because various reports indicate that the asymptomatic cases will spread the disease more than the symptomatic cases. The model is proved to be mathematically well-posed and biologically meaningful by showing positivity and boundedness of the solution using the appropriate initial conditions. For the reproduction number, a parametric formula is constructed, and also the associated numerical value is calculated from the reported real data in Ethiopia. Moreover, disease-free and endemic equilibria are determined, and their local and global stabilities are discussed using the Lyapunov function technique. These equilibria are found to be locally asymptotically stable if R 0 < 1 and R 0 > 1 , respectively. Following the model fitting and estimation of the parameter values, sensitivity analysis was performed in order to analyze the impact of each parameter on transmission dynamics. In other words, this study can be used to evaluate how major model parameters affect transmission dynamics and control. Utilizing Pontryagin’s maximal principle, the best control measures are implemented with the aim of lowering the burdens associated with infection, prevention, and treatment. To comprehend and visualize the impact of control techniques on the development of the disease and to illustrate the analytical findings generated in this study, numerical simulation studies are conducted. Finally, the output of the study illustrates that adhering to all the control strategies has a big impact on minimizing the transmission of the disease in society. Which means that if the control strategies are well managed by the concerned body, then the burden of the disease is reduced quickly in the Ethiopian population.
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