Title of article :
Modelling the Occurrence of the Novel Pandemic COVID-19 Outbreak in Nigeria: A Box and Jenkins Approach
Author/Authors :
Nurudeena, A. Department of Statistics - Federal University of Agriculture, Abeokuta, Nigeria , Isqeela, O. Department of Statistics - Federal University of Agriculture, Abeokuta, Nigeria , Saddam, D. Department of Statistics - Ahmadu Bello University, Zaria, Nigeria
Abstract :
The coronavirus disease 2019 (COVID-19) is a novel pandemic disease that spreads
very fast and causes severe respiratory problem to its carrier and thereby results to death in some
cases. In this research, we studied the trend, model Nigeria daily COVID-19 cases and forecast for
the future occurrences in the country at large. We adopt the Box and Jenkins approach. The time
plot showed that the cases of COVID-19 rises rapidly in recent time. KPSS test confirms the
non-stationarity of the process (p < 0.05) before differencing. The test also confirmed the
stationarity of the process (p > 0.05) after differencing. Various ARIMA (p,d,q) were examined
with their respective AICs and Log-likelihood. ARIMA (1, 2, 1) was selected as the best model
due to its least AIC (559.74) and highest log likelihood (-276.87). Both Shapiro-Wilk test and Box
test performed confirm the fitness of the model (p > 0.05) for the series. Forecast for 30 days was
then made for COVID-19 cases in Nigeria. Conclusively, the model obtained in this research can
be used to model, monitor and forecast the daily occurrence of COVID-19 cases in Nigeria.
Farsi abstract :
فاقد چكيده فارسي
Keywords :
COVID-19 , Modell , Forecast , AIC , Log–likelihood.
Journal title :
International Journal of Mathematical Modelling and Computations