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http://dx.doi.org/10.6109/jkiice.2022.26.1.58

Prediction of Covid-19 confirmed number of cases using SARIMA model  

Kim, Jae-Ho (Department of Computer Science, The University of Suwon)
Kim, Jang-Young (Department of Computer Science, The University of Suwon)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.26, no.1, 2022 , pp. 58-63 More about this Journal
Abstract
The daily number of confirmed cases of Coronavirus disease 2019(COVID-19) ranges between 1,000 and 2,000. Despite higher vaccination rates, the number of confirmed cases continues to increase. The Mu variant of COVID-19 reported in some countries by WHO has been identified in Korea. In this study, we predicted the number of confirmed COVID-19 cases in Korea using the SARIMA for the Covid-19 prevention strategy. Trends and seasonality were observed in the data, and the ADF Test and KPSS Test was used accordingly. Order determination of the SARIMA(p,d,q)(P, D, Q, S) model helped in extracting the values of p, d, q, P, D, and Q parameters. After deducing the p and q parameters using ACF and PACF, the data were transformed and schematized into stationary forms through difference, log transformation, and seasonality removal. If seasonality appears, first determine S, then SARIMA P, D, Q, and finally determine ARIMA p, d, q using ACF and PACF for the order excluding seasonality.
Keywords
Seasonal auto regressive integrated moving average(SARIMA); Covid-19; Augmented dickey-fuller(ADF) test; Kwiatkowski-phillips-schmidt-shin(KPSS) test;
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