Will Covid-19 cases in the World reach 4 million? a forecasting approach using SutteARIMA

Ansari Saleh Ahmar - Business School, Universitat de Barcelona, Spain Department of Statistics, Universitas Negeri Makassar, Indonesia
R. Rusli - Department of Mathematics, Universitas Negeri Makassar, Indonesia


Citation Format:



DOI: http://dx.doi.org/10.30630/joiv.4.3.389

Abstract


The objective of this study was to determine whether Covid-19 cases in the world would have reached 4 million cases with the SutteARIMA method forecasting approach. Data from this study were obtained from the Worldometer from 1 March 2020 to 05 May 2020. Data were used for data fitting from 1 March 2020 to 28 April 2020 (29 April 2020 – 05 May 2020). The data fitting is used to see the extent of the accuracy of the SutteARIMA method when predicting data. The MAPE method is used to see the level of data accuracy. Results of forecasting data for the period from 29 April 2020 to 05 May 2020: 72,731; 84,666; 92,297; 100,797; 84,312; 81,517; 74845. The accuracy of SutteARIMA for the period 30 April 2020 – 06 May 2020 shall be 0.069%. Forecast results for as many as 4 million cases, namely from 08 May 2020 to 10 May 2020: 3,966,786; 4,047,328 and 4,127,747. The SutteARIMA method predicts that 4 million cases of Covid-19 in the world will be reported on the WHO situation report on the day 110/111 or 09 May 2020/10 May 2020.

Keywords


Covid-19; short-term forecast; SutteARIMA

Full Text:

PDF

References


Yang Y, Peng F, Wang R, Guan K, Jiang T, Xu G, et al. The deadly coronaviruses: The 2003 SARS pandemic and the 2020 novel coronavirus epidemic in China. J Autoimmun 2020:102434. https://doi.org/10.1016/j.jaut.2020.102434.

Worldometer. COVID-19 Coronavirus Pandemic. https://www.worldometers.info/coronavirus (accessed May 6, 2020).

Koczkodaj WW, Mansournia MA, Pedrycz W, Wolny-Dominiak A, Zabrodskii PF, Strzaška D, et al. 1,000,000 cases of COVID-19 outside of China: The date predicted by a simple heuristic. Glob Epidemiol 2020:100023. https://doi.org/10.1016/j.gloepi.2020.100023.

Ahmar AS, del Val EB. SutteARIMA: Short-term forecasting method, a case: Covid-19 and stock market in Spain. Sci Total Environ 2020:138883. https://doi.org/10.1016/j.scitotenv.2020.138883.

Wei WWS. Time Series Analysis: Univariate and Multivariate Methods. New York: Addison-Wesley Publishing Company; 1994.

Ahmar AS, Rahman A, Mulbar U. α-Sutte Indicator: A new method for time series forecasting. J. Phys. Conf. Ser., vol. 1040, 2018. https://doi.org/10.1088/1742-6596/1040/1/012018.

Ahmar AS. A Comparison of α-Sutte Indicator and ARIMA Methods in Renewable Energy Forecasting in Indonesia. Int J Eng Technol 2018;7:20–2.