On Statistical Analysis of Forecasting COVID-19 for the Upcoming Months in the Kingdom of Saudi Arabia


  • Bachioua Lahcene Department of Basic Sciences Prep, Year, P.O. Box 2440, University of Ha’il, Ha’il, Saudi Arabia




Time Series, Traffic Accidents, Automatic Integrated Average Regression Model, Forecasting, Best Practices, COVID-19, Kingdom of Saudi Arabia.


This paper presents a statistical analysis using fitted prediction models that revealed a high exponential growth in the number of confirmed cases, deaths, and treated case processes based on our model predictions and the results of experimental COVID-19 predictions. The studies aimed to build inductive statistical models using the automatic integrated mean regression model methodology, and its preferred method for tracking data that represent the spread of the epidemic and then effectively predicting its numbers over the next six months, in addition to the number of deaths and cases that responded to recovery treatment using ARIMA.

Moreover, the number of infected cases per day is expected to stabilize less than 500, daily deaths are less than 15, and this situation will continue until the largest number of people are vaccinated in order to obtain herd immunity, and control the causes of the spread of the epidemic such as human gatherings and friction. Among individuals, in addition to obtaining the appropriate vaccine in the future, especially since the Kingdom of Saudi Arabia is waiting for this year's pilgrims from inside and outside the Kingdom, the results of this work will be useful for practitioners in various fields of theoretical and applied sciences.




How to Cite

Lahcene, B. . (2021). On Statistical Analysis of Forecasting COVID-19 for the Upcoming Months in the Kingdom of Saudi Arabia. International Journal of Statistics in Medical Research, 10, 22–29. https://doi.org/10.6000/1929-6029.2021.10.03



General Articles