Stability Analysis of Mathematical Modeling of Interaction between Target Cells and COVID-19 Infected Cells

S. Sugiyanto, M. A. Hamid, Alya Adianta, Hanny Puspha Jayanti, Muhammad Ja’far Luthfi
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Abstract

The stability analysis in this mathematical model was related to the infection of the Coronavirus Disease 2019 (Covid-19). In this mathematical model there were two balance points, namely the point of balance free from Covid-19 and the one infected with Covid-19. The stability of the equilibrium point was influenced by all parameters, i.e. target cells die during each cycle, number of target cells at  = 0, target cells infected during each cycle based on virion unit density, effective surface area of the network, the ratio of the number of virus particles to the number of virions, infected cells die during each cycle, the number of virus particles produced by each infected cell during each cycle, and virus particles die during each cycle. In the simulation model, immunity is divided into high, medium and low immunity. For high, moderate and low immunity, respectively, the highest number of target cells is in high, medium and low immunity, whereas for the number of infected cells and the number of Covid-19, it is in the opposite sequence of the number of target cells.
靶细胞与COVID-19感染细胞相互作用数学模型的稳定性分析
该数学模型的稳定性分析与2019冠状病毒病感染有关。在该数学模型中存在两个平衡点,即没有Covid-19的平衡点和感染Covid-19的平衡点。平衡点的稳定性是影响参数,即目标细胞死亡在每个周期中,靶细胞的数量= 0,在每个周期基于靶细胞感染病毒粒子单元密度,有效表面积的网络,病毒颗粒的数量比病毒粒子的数量,受感染的细胞死亡在每个周期,每个受感染的细胞产生的病毒颗粒的数量在每个周期,和病毒粒子死在每个周期。在仿真模型中,免疫度分为高、中、低免疫度。对于高、中、低免疫,靶细胞数量分别为高、中、低免疫,而感染细胞数量和新冠病毒数量与靶细胞数量顺序相反。
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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