Forecasting the Number of Coronavirus (COVID-19) Cases in Ethiopia Using Exponential Smoothing Times Series Model

Abstract

Coronavirus, also known as COVID-19 was first originated in Wuhan, Hubei province in China around December 2019 andspread out all over the world within few weeks. Following the outbreak, the World Health Organization (WHO) declares the outbreak as pandemic on 11 March 2019. The coronavirus (COVID-19) have a fast transmission nature and grow exponentially across the globe. Subsequently, to model the exponential growing nature of the virus, different researchers conducted their study using a linear based time series (such as ARMA family) models. However, such linear time series models cannot handle data having an exponential growing pattern. Since linear based time series models cannot handle a data having an exponential growing pattern, we applied the common exponential family models such as an Exponential Growth Model, Simple Exponential Smoothing (SES), and Double Exponential Smoothing (DES) methods in Ethiopia from March 14, 2020 to June 05, 2020. The results of the study showed that double exponential smoothing methods was appropriate in forecasting the future number of COVID-19 cases in Ethiopia as dictated by lowest value of root mean sum of square error. The forecasting model shows that the number of coronavirus cases in Ethiopia grows exponentially. In general, the forecast helps the Ethiopian government, policy makers, and the society at all to take preventive measures before the transmission become out of control especially rural areas since until now, most of the cases were observed in urban areas.