Predicting Using Time-Series Models who are Exposed to Coronavirus Infection, Recovered, and Died From it in Some Arab Countries

Abstract. The deadly Corona virus pandemic continues to spread in its various strains, at a crazy speed in recent months, and despite the multiple vaccinations of its first and second types and with its various names all over the world, the pandemic continues to surprise the health authorities and restrict their plans to manage the future of the crisis. Assuming that government service institutions are needed by individuals to resume the new normal life carefully, and for this reason governments need to adopt effective decisions that lead to facilitating life matters. This study uses data analysis from December 2021 to May 2022 to simulate the models adopted in modeling and simulation.
Two different scenarios were developed to predict the fluctuating trends and dynamics of the epidemic, through general stochastic models, to better estimate its extent, and the future outcomes of this epidemic.
Time series models, especially ARIMA series and logistic growth, have shown excellent performance in predicting the spread of the epidemic, its trends and dynamics at different stages during the previous two years. And the policies applied to it, determining the amount of resources needed to manage the different stages and dealing with the final volume of epidemic estimates and imposing more precautions.
The ultimate goal of this paper was to modify and enhance the mathematical modeling to guide the health authority and help it in the early assessment of the outbreak of the epidemic and foreseeing the paths of the epidemic. Short and long-term forecasts of the prevalence and dynamics of COVID-19.