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

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.