Department of Statistics, College of Natural and Computational Science, Mekelle University, P.O. Box 231, Mekelle, Ethiopia
Research
Modeling and Forecasting the Global Daily Incidence of Novel Coronavirus Disease (COVID-19): An Application of Autoregressive Moving Average (ARMA) Model
Author(s): Amare Wubishet Ayele*, Mulugeta Aklilu Zewdie and Tizazu Bayko
Background: Coronavirus disease (Covid-19) is a public health epidemic outbreak and is currently a concern of the international community.
As of 23 March 2020, the number of confirmed cases of COVID-19 has reached more than 300,000 worldwide. This burden crates high stress
in the global community, and is having a significant impact on the global economy. This paper pursued to obtain a time series model that able
to model and forecast the global daily incidence of Novel Coronavirus disease (COVID-19).
Methods: Global daily number of confirmed cases and deaths from Novel Coronavirus (COVID-19) reported during the study period from
22 January 2020 to 22 March 2020 were considered. A time series model namely an Autoregressive Moving Average (ARMA) Model was
employed to model and forecast the daily global incidence of COVID-19. Va.. Read More»
DOI:
10.37421/2736-6189.2020.5.202
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