期刊
INFECTIOUS DISEASE MODELLING
卷 6, 期 -, 页码 678-692出版社
KEAI PUBLISHING LTD
DOI: 10.1016/j.idm.2021.04.005
关键词
COVID-19; Jacobian matrix; Lyapunov stability; Reproduction number; SEIR model; SEIQR model
资金
- Research and Development Grants Program for National Research Institutions and Centres (GRANTS)
- Target Research Program, Infectious Diseases Research Grant Program, King Abdulaziz City for Science and Technology (KACST), and Kingdom of Saudi Arabia [5-20-01-0070002]
This study established a mathematical epidemic model for the outbreak of COVID-19 and used real data from Saudi Arabia for analysis and validation. The SEIQR model was proven effective in analyzing epidemic spread.
This article attempts to establish a mathematical epidemic model for the outbreak of the new COVID-19 coronavirus. A new consideration for evaluating and controlling the COVID-19 outbreak will be constructed based on the SEIQR Pandemic Model. In this paper, the real data of COVID-19 spread in Saudi Arabia has been used for the mathematical model and dynamic analyses. Including the new reproductive number and detailed stability analysis, the dynamics of the proposed SEIQR model have been applied. The local sensitivity of the reproduction number has been analyzed. The domain of solution and equilibrium based on the SEIQR model have been proved using a Jacobian linearization process. The state of equilibrium and its significance have been proved, and a study of the integrity of the disease-free equilibrium has been carried out. The Lyapunov stability theorem demonstrated the global stability of the current model equilibrium. The SEIQR model has been numerically validated and projected by contrasting the results from the SEIQR model with the actual COVID-19 spread data in Saudi Arabia. The result of this paper shows that the SEIQR model is a model that is effective in analyzing epidemic spread, such as COVID-19. At the end of the study, we have implemented the protocol which helped the Saudi population to stop the spread of COVID-19 rapidly. (C) 2021 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.
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