Studying the Spread of COVID-19 and Its Impact on E-learning: from a Deep Learning Perspective

COVID-19 is a respiratory infectious disease caused by a recently discovered Coronavirus. Since December 2019 and as of October 8, 2020, about 36.6 million (36,625,199) confirmed cases of COVID-19 have been registered globally by theWHO, with more than 1million (1,063,780) deaths. This paper investigates statistically the spread of COVID-19 disease, which became a killer pandemic in Saudi Arabia. We demonstrate that the low apparent Case Fatality Ratio (CFR) (i.e., mortality rate) observed in Saudi Arabia, as compared with other countries, is strongly proportional to the number of infection cases. To present an effective statistical analysis of the end of COVID-19 pandemic, the researchers used the present evaluation of the Infection Fatality Ratio (IFR) of the COVID-19 reported until September 2020, depending on the reported CFR obtained from the Ministry of Health. The proposed analysis shows more realistic evaluations of the actual range of the deceased as well as more precise factors of how rapidly the infection spreads. The study demonstrates the more powerful elements causing the seriousness of the COVID-19 in Saudi Arabia. Finally, the researchers use the mortality number collected through the last seven months to predict both the overall number of infections and the period in which the infection will end in the Kingdom of Saudi Arabia. The researchers presented the effect of the spread of the COVID-19 pandemic in the E-learning sector in the KKU and BUE universities and the period in which the infection will end. Deep learning (DL) is a potentially powerful artificial intelligence (AI) tool in the fight against the COVID-19 pandemic. This paper also addressed this issue and answered the question: can deep learning technology be used to early screen COVID-19 patients from their computed tomography (CT) images and what is the accuracy of this diagnostic tool.