COVID-19 in Saudi Arabia: Real Data and Simulation for Impact Prediction - A Case Study

Abstract

The start of the COVID-19 pandemic in early 2020 has caused trouble all over the world. This contagious disease is mostly spread by people, and it spreads much faster than other flu viruses that have been found before. Although vaccines have been discovered and are functional, it will still be the greatest challenge to conquer this disease. To effectively respond to this unprecedented crisis and save human lives from other infectious diseases in the future, it is crucial to better understand how the virus is transmitted from one host to another and how future zones of contagion can be anticipated. Several waves of infection have hit nations worldwide for almost the last four years, and governments have implemented necessary measures to tackle the spread of the virus. However, mathematical modeling has emerged as a powerful tool to inform decision-making, allowing for the prediction of COVID-19’s effects. In this research article, we investigate the impact of COVID-19 in Saudi Arabia using the three most commonly used mathematical models: the classic SIR (Susceptible-Infected-Recovered) model, the extended SEIR (Susceptible-Exposed-Infected-Recovered) model, and the advanced fractional-order models using freely available real recorded data for research. By incorporating actual data from Saudi Arabia and utilizing three simulation techniques, we strive to provide valuable insights into the dynamics of the pandemic and aid in the formulation of effective strategies to control its spread in Saudi Arabia.