Shakhany Mohammad Qaleh, Salimifard Khodakaram
Persian Gulf University, Computational Intelligence & Intelligent Research Group, Mahini Street, Bushehr 75169-13798.
Chaos Solitons Fractals. 2021 May;146:110823. doi: 10.1016/j.chaos.2021.110823. Epub 2021 Mar 11.
This paper uses transformed subsystem of ordinary differential equation model, with vital dynamics of birth and death rates, and temporary immunity (of infectious individuals or vaccinated susceptible) to evaluate the disease-free and endemic equilibrium points, using the Jacobian matrix eigenvalues of both disease-free equilibrium and endemic equilibrium for COVID-19 infectious disease to show and ratios to the population in time-series. In order to obtain the disease-free equilibrium point, globally asymptotically stable ( ), the effect of control strategies has been added to the model (in order to decrease transmission rate and reinforce susceptible to recovered flow), to determine how much they are effective, in a mass immunization program. The effect of transmission rates (from to ) and (from to ) varies, and when vaccination effect , is added to the model, disease-free equilibrium is globally asymptotically stable, and the endemic equilibrium point , is locally unstable. The initial conditions for the decrease in transmission rates of and reached the corresponding disease-free equilibrium locally unstable, and globally asymptotically stable for endemic equilibrium . The initial conditions for the decrease in transmission rate and and increase in reached the corresponding disease-free equilibrium globally asymptotically stable, and locally unstable in endemic equilibrium .
本文使用常微分方程模型的变换子系统，结合出生和死亡率的生命动力学以及（感染个体或接种疫苗的易感者的）暂时免疫力，来评估无病平衡点和地方病平衡点，并利用COVID-19传染病无病平衡点和地方病平衡点的雅可比矩阵特征值在时间序列中展示与种群的关系和比例。为了获得全局渐近稳定的无病平衡点（ ），已将控制策略的影响添加到模型中（以降低传播率并加强易感者到康复者的流动），以确定它们在大规模免疫计划中的有效程度。传播率 （从 到 ）和 （从 到 ）的影响各不相同，并且当将疫苗接种效果 加入模型时，无病平衡点是全局渐近稳定的，而地方病平衡点 是局部不稳定的。传播率 和 下降的初始条件在局部达到相应的无病平衡点不稳定，而在地方病平衡点全局渐近稳定。传播率 和 下降以及 增加的初始条件在全局达到相应的无病平衡点渐近稳定，而在地方病平衡点局部不稳定。
