Modeling and Forecasting for the number of cases of the COVID-19 pandemic with the Curve Estimation Models, the Box-Jenkins and Exponential Smoothing Methods

Özet

Objectives: The aim of this study is to present statistical information summarizing the general structure about the effects and process of infection in all countries of the world in the light of the data obtained and to model the daily change of infection criteria. Methods: The number of COVID 19 epidemic cases of the selected countries of G8 countries, Germany, United Kingdom, France, Italy, Russian, Canada, Japan, and Turkey between 1/22/2020 and 3/22/2020 has been estimated and forecasted by using some curve estimation models, Box-Jenkins (ARIMA) and Brown/Holt linear exponential smoothing methods in this study. Results: Japan (Holt Model), Germany (ARIMA (1,4.0)) and France (ARIMA (0,1,3)) provide statistically significant but not clinically qualified results in this data set. UK (Holt Model), Canada (Holt Model), Italy (Holt Model) and Turkey (ARIMA (1,4,0)) and in the results are more reliable. Specified for the particular model used in this case Turkey. Conclusion: In future studies, more data and healthier evaluations can be made as a matter of course. However, since this study provides information about the levels that the number of cases can reach if the course of the current situation cannot be intervened, it can guide countries to take the necessary measures and to intervene early.