Open J Public Health | Volume 4, Issue 2 | Research Article | Open Access

Time Series Model to Forecasting the New Coronavirus Case in Ethiopia

Kindu Kebede1*, Fasiledes Fetene2 and Hailemichael Menberu3

1Department of Statistics, College of Computing and Informatics, Haramaya University, Ethiopia 2Department of Statistics, College of Computational Science, Woldiya University, Ethiopia 3Department of Statistics, College of Computational Science, Wolayita Sodo University, Ethiopia

*Correspondance to: Kindu Kebede 

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Abstract

Background: Coronaviruses are a large family of respiratory viruses that can cause illness in people. The goal of this study is find an appropriate model and forecast the new cases in Ethiopia. Methods: ARIMA models are the most general class of models for forecasting a time series data. The ARIMA forecasting equation for a stationary time series is a linear equation in which the predictors consist of lags of the dependent variable or lags of the forecast errors. Results: In Ethiopia the daily average increment in COVID-19 from March 14th, 2020 to September 13th, 2020 was 347. The maximum value of new cases recorded in Ethiopia was 1829 on August 22nd, 2020. The series is not stationary at level, but the series is stationary at first difference. The selected model in this study was ARIMA (1,1,2) that has small AIC and BIC. Conclusion: This study focused on find an appropriate model and forecast the new cases in Ethiopia. Based on ARIMA (1,1,2) model the new cases in Ethiopia was 808 people with CI [482,1134] and 532 people with CI [-281,1344] from September 14th, 2020 and September 30th, 2020.

Keywords:

Coronavirus; Forecasting; Autoregressive integrative moving average; Stationary; Ethiopia

Citation:

Kebede K, Fetene F, Menberu H. Time Series Model to Forecasting the New Coronavirus Case in Ethiopia. Open J Public Health. 2022; 4(2): 1033..

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