Predicting of COVID-19 Confirmed Cases in Different Countries with ARIMA Models in 2020

Abstract

Abstract The epidemic of a novel coronavirus illness (COVID-19) becomes as a global threat. The aim of this study is first to find the best prediction models for daily confirmed cases in countries with high number of confirmed cases in the world and second to predict confirmed cases with these models in order to have more readiness in healthcare systems. This study was conducted based on daily confirmed cases of COVID-19 that were collected from the official website of Johns Hopkins University from January 22 th , 2020 to March 1 th , 2020. Auto Regressive Integrated Moving Average (ARIMA) model was used to predict the trend of confirmed cases. Stata version 12 and R version 3.6.2 were used. Parameters used for ARIMA were (2,1,0) for Mainland China, ARIMA(1,0,0) for South Korea, and ARIMA(3,1,0) for Thailand. Mainland China and Thailand were successful in haltering COVID-19 epidemic. Investigating their protocol in this control like quarantine should be in the first line of other countries’ program