In this paper, we use forecasting methods such as Euler’s iterative method and cubic spline interpolation to predict the total number of people infected and the number of active cases for COVID-19 propagation. We construct a novel iterative method, which is based on cubic spline interpolation and Euler’s method and it is an improvement over the two latter methods. The novel method is very efficient for forecasting and to describe the underlying dynamics of the pandemic. Our predicted results are also compared with an iterative method developed by Perc et al. [1]. Our study encompasses the following countries namely; South Korea, India, South Africa, Germany, and Italy. We use data from 15 February 2020 to 31 May 2020 in order to obtain graphs and then obtain predicted values as from 01 June 2020. We use two criteria to classify whether the predicted value for a certain day is effective or not.

在本文中，我们使用诸如Euler迭代法和三次样条插值法的预测方法来预测感染人数和COVID-19传播的活跃病例数。我们构建了一种新颖的迭代方法，该方法基于三次样条插值和欧拉方法，是对后两种方法的改进。该新方法对于预测和描述大流行的基本动态非常有效。我们的预测结果也与Perc等人开发的迭代方法进行了比较。[1]。我们的研究涵盖以下国家：韩国，印度，南非，德国和意大利。我们使用2020年2月15日至2020年5月31日的数据来获取图表，然后获取2020年6月1日以来的预测值。