A New Dynamical Modelling of the Epidemic Diseases to Assessing the Rates of Spread of COVID-19 in Saudi Arabia: SEIRQ Model

Hamdy Youssef, Najat Alghamdi, Magdy Ezzat, Alaa El-Bary, Ahmed Shawky

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Received date: 10th September 2020

A new model of critical epidemic dynamics for the emergence of the new coronavirus COVID-19 is being established in this paper. A new approach to the assessment and control of the COVID 19 epidemic is given with the SEIRQ pandemic model. This paper uses real knowledge on the distribution of COVID-19 in Saudi Arabia for mathematical modeling and dynamic analyses. The reproductive number and detailed stability analysis are provided in the SEIRQ model dynamics. In a Jacobian method of linearization, we will address the domain of the solution and the equilibrium situation based on the SEIRQ model. The equilibrium and its importance have been proven, and a study of the stability of the equilibrium free from diseases has been implemented. The reproduction number was evaluated in accordance with its internal parameters. The Lyapunov theorem of stability has proven the global stability of the current model's equilibrium. The SEIRQ model was contrasted by comparing the results based on the SEIRQ model with the real COVID-19 spread data in Saudi Arabia. Numerical evaluation and predictions were given. The results indicate that the SEIRQ model is a strong model for the study of the spread of epidemics, such as COVID-19. At the end of this work, we implemented an optimum protocol that can quickly stop the spread of COVID-19 among the Saudi populations.

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This is an abstract of a preprint hosted on a preprint server, which is currently undergoing peer review at Scientific Reports. The findings have yet to be thoroughly evaluated, nor has a decision on ultimate publication been made. Therefore, the results reported should not be considered conclusive, and these findings should not be used to inform clinical practice, or public health policy, or be promoted as verified information.

Scientific Reports

Nature Research, Springer Nature