Forecast number of new cases of Corona Virus Disease (COVID-19) in Ethiopia, using the case-based autoregressive integrated moving average model - Alemu Bekele Eticha (Open Journal of Bioinformatics and Biostatistics - Peertechz Publications, 2020)
After the initial outbreak in Ethiopia, the dispersion of SARS-CoV-2 is elevated number of cases. Literally, reported results for confirmed cases peaked in August 2020 and declined after that time, as evidenced by the contestd responses that have invested in pandemic control in the country. ARIMA models are a most widely used approaches to time series forecasting and provide harmonizing approaches to the problem of forecasting. ARIMA models aim to describe autocorrelations in the data. Thus, in this study, the Autoregressive Integrated Moving Average (ARIMA) method is used to predict the number of new coronavirus cases. In short, Auto regression uses the dependent relationship between observation and lagged observations; Integrated using the difference in raw observations; and Moving Average relies on the dependency between observation and residual error.  ARIMA (2, 2, 2) predicts the number of confirmed cases of COVID-19, based on the period between March 2020 and December 2020 at 95% confidence intervals. The result revealed that the maximum expected new case per day was 807 and the minimum forecast was 410 cases per day in the next two months. In addition, the total number of confirmed COVID-19 expected cases could reach about 160585 by end-February 2021. In general, if the government of Ethiopia stops controlling the COVID-19 mechanisms the pandemic may relapse severely and affect the country more. The study therefore proposed that the constructive stepladder incorporates control mechanisms. Thus, depending on the results of the report, all the organizations involved will establish policies.