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Analysing COVID-19 Verified, Recuperate and Death Cases in Ethiopia Using ARIMA Models


Birhanu Betela Warssamo

Abstract

Applying a successful prediction of the confirmed, recovered and deaths is thought to be the basic requirement to successfully control the spreading rate of diseases. Time series models have extensively been considered as the suitable methods to forecast the confirmed, recovered and deaths because of the virus. The aim of this research is to apply the Autoregressive Integrated Moving Average (ARIMA) modelling approach for projectingCOVID-19 confirmed, recovered and deaths cases in Ethiopia. Over strict follows of all phases of Box-Jenkins strategy, ARIMA (1,1,1), ARIMA (16,1,2), and ARIMA (0,1,1)models for confirmed case, recovered and death case, respectively were selected as the best models for predicting coronavirus cases of Ethiopia. Using these models, a forecast of five-month a heads future situation of COVID-19 confirmed case, recovered and death case (Jan 3, 2021 to May 3, 2021) has been made. The results showed that in the coming five months from Jan 3, 2020 to May 3, 2021, the number of COVID-19 confirmed, recovered and deaths cases in Ethiopia may reach up to 320,597; 168,912 and 4438, respectively. Generally, the size of the coronavirus distribution was increased from time to time in the past ten months, until 3rd Jan, 2021, and it is expected to continue quicker than before for the coming 5-months, until the end of May, 2021, in Ethiopia and more rapidly than before while the peak will remain unknown yet. Therefore, effective implementation of the preventive measures and a rigorous compliance by avoiding negligence with the rules such as prohibiting public gatherings, travel restrictions, personal protection measures, and social distancing may improve the spreading rates of the virus. Further, through updating more new data with a continuous reconsideration of predictive model provide useful and more precise prediction


Journal Identifiers


eISSN: 2789-3618
print ISSN: 2789-360X