论文标题
COVID-19模型中的数据预测，并向我们，韩国，巴西，印度，俄罗斯和意大利申请
The Data Forecast in COVID-19 Model with Applications to US, South Korea, Brazil, India, Russia and Italy
论文作者
论文摘要
在本文中，我们首先提出SQIARD和SIARD模型，以研究Covid-19与隔离，感染和无症状感染的Covid-19的传播，并讨论相应的基本繁殖数字$ R_0，R_Q $与模型平衡点的稳定性之间的关系。其次，在培训相关数据参数之后，在我们的数值模拟中，我们分别进行了我们，韩国，韩国，巴西，印度，俄罗斯和意大利数据的预测，以及对每个国家流行病状况的影响。此外，我们将我们的数据应用于将SQIARD与Siard进行比较，并显示预测的效果。
In this paper, we firstly propose SQIARD and SIARD models to investigate the transmission of COVID-19 with quarantine, infected and asymptomatic infected, and discuss the relation between the respective basic reproduction number $R_0, R_Q$ and the stability of the equilibrium points of model. Secondly, after training the related data parameters, in our numerical simulations, we respectively conduct the forecast of the data of US, South Korea, Brazil, India, Russia and Italy, and the effect of prediction of the epidemic situation in each country. Furthermore, we apply US data to compare SQIARD with SIARD, and display the effects of predictions.
