Ndondo A M, Kasereka S K, Bisuta S F, Kyamakya K, Doungmo E F G, Ngoie R-B M
University of Lubumbashi, Mathematics and Computer Science Department, Lubumbashi, Democratic Republic of the Congo.
Artificial intelligence, BIg data and modeLing simulation Research Center (ABIL), Kinshasa, Democratic Republic of the Congo.
Results Phys. 2021 May;24:104096. doi: 10.1016/j.rinp.2021.104096. Epub 2021 Mar 27.
This paper deals with modeling and simulation of the novel coronavirus in which the infectious individuals are divided into three subgroups representing three forms of infection. The rigorous analysis of the mathematical model is provided. We provide also a rigorous derivation of the basic reproduction number . For , we prove that the Disease Free Equilibium (DFE) is Globally Asymptotically Stable (GAS), thus COVID-19 extincts; whereas for , we found the co-existing phenomena under some assumptions and parametric values. Elasticity indices for with respect to different parameters are calculated with baseline parameter values estimated. We also prove that a transcritical bifurcation occurs at . Taking into account the control strategies like screening, treatment and isolation (social distancing measures), we present the optimal control problem of minimizing the cost due to the application of these measures. By reducing the values of some parameters, such as death rates (representing a management effort for all categories of people) and recovered rates (representing the action of reduction in transmission, improved screening, treatment for individuals diagnosed positive to COVID-19 and the implementation of barrier measures limiting contamination for undiagnosed individuals), it appears that after days, the peak of the pandemic is reached and shows that by continuing with this strategy, COVID-19 could be eliminated in the population.
本文研究新型冠状病毒的建模与仿真,其中将感染个体分为三个亚组,代表三种感染形式。对该数学模型进行了严格分析。我们还给出了基本再生数的严格推导。对于 ,我们证明无病平衡点(DFE)是全局渐近稳定的(GAS),因此新冠病毒将灭绝;而对于 ,我们在一些假设和参数值下发现了共存现象。利用估计的基线参数值计算了 相对于不同参数的弹性指数。我们还证明在 处发生跨临界分岔。考虑到筛查、治疗和隔离(社交距离措施)等控制策略,我们提出了使因应用这些措施而产生的成本最小化的最优控制问题。通过降低一些参数的值,如死亡率(代表对所有人群的管理努力)和康复率(代表减少传播的行动、改进筛查、对新冠病毒检测呈阳性的个体进行治疗以及对未确诊个体实施限制感染的屏障措施),似乎在 天后达到疫情高峰,并表明通过继续实施该策略,新冠病毒可在人群中被消除。