International Journal of Statistics and Applied Mathematics
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International Journal of Statistics and Applied Mathematics

2022, Vol. 7, Issue 3, Part A

Predictive accuracy of time series model using COVID-19 cases in Eastern Visayas


Author(s): Urbano P Pino Jr., Thea C Galos, Rizaldo Louis E Penetrante and Jhon Dexther G Yaras

Abstract: SARS-Cov-2 is a novel coronavirus strain that has not previously been associated with human infection. COVID-19 is the name given to the disease caused by SARS-Cov-2. The World Health Organization declared it a Public Health Emergency of International Concern on January 30, 2020, and was later declared a pandemic on March 11, 2020. In this paper, we used MAD, MAPE, and RMSE to measure the predictive accuracy of the forecasting models for the COVID-19 cases of the provinces/cities in the region, namely, Biliran, Eastern Samar, Northern Samar, Samar, Leyte, Southern Leyte, Tacloban City, and Ormoc City. The data for this study comes from an official COVID-19 cases dataset provided by the Regional Epidemiology & Surveillance Unit of Department of Health (DOH) – Eastern Visayas Center for Health and Development from March 1, 2020 to October 30, 2021. The dataset contains confirmed cases on a weekly basis for 87 weeks (79 weeks were used for forecasting and 8 weeks were used to determine the predictive accuracy). From the results, it has been found out that ARIMA models can be highly reliable in forecasting the cases in Eastern Visayas.

DOI: 10.22271/maths.2022.v7.i3a.818

Pages: 13-16 | Views: 167 | Downloads: 49

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How to cite this article:
Urbano P Pino Jr., Thea C Galos, Rizaldo Louis E Penetrante, Jhon Dexther G Yaras. Predictive accuracy of time series model using COVID-19 cases in Eastern Visayas. Int J Stat Appl Math 2022;7(3):13-16. DOI: 10.22271/maths.2022.v7.i3a.818
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