Olumuyiwa James Peter, Hasan S. Panigoro, Afeez Abidemi, Mayowa M. Ojo, Festus Abiodun Oguntolu
This paper is concerned with the formulation and analysis of an epidemic model of COVID-19 governed by an eight-dimensional system of ordinary differential equations, by taking into account the first dose and the second dose of vaccinated individuals in the population. The developed model is analyzed and the threshold quantity known as the control reproduction number R is obtained. We investigate the equilibrium stability of the system, and the COVID-free equilibrium is said to be locally asymptotically stable when the control reproduction number is less than unity, and unstable otherwise. Using the least-squares method, the model is calibrated based on the cumulative number of COVID-19 reported cases and available information about the mass vaccine administration in Malaysia between the 24th of February 2021 and February 2022. Following the model fitting and estimation of the parameter values, a global sensitivity analysis was performed by using the Partial Rank Correlation Coefficient (PRCC) to determine the most influential parameters on the threshold quantities. The result shows that the effective transmission rate (α) , the rate of first vaccine dose (ϕ) , the second dose vaccination rate (σ) and the recovery rate due to the second dose of vaccination (η) are the most influential of all the model parameters. We further investigate the impact of these parameters by performing a numerical simulation on the developed COVID-19 model. The result of the study shows that adhering to the preventive measures has a huge impact on reducing the spread of the disease in the population. Particularly, an increase in both the first and second dose vaccination rates reduces the number of infected individuals, thus reducing the disease burden in the population. © 2023, Prof. Dr. Jan van der Hoeven stichting voor theoretische biologie.
Department of Mathematical and Computer Sciences, University of Medical Sciences, Ondo State, Ondo City, Nigeria; Department of Epidemiology and Biostatistics, School of Public Health, University of Medical Sciences, Ondo State, Ondo City, Nigeria; Department of Mathematics, State University of Gorontalo, Bone Bolango, 96119, Indonesia; Department of Mathematical Sciences, Federal University of Technology, Ondo State, Akure, Nigeria; Department of Mathematical Sciences, Universiti Teknologi Malaysia, Johor, Johor Bahru, Malaysia; Department of Mathematical Sciences, University of South Africa, Florida, South Africa; Microbiology Division, Thermo Fisher Scientific, Lenexa, KS, United States; Department of Mathematics, Federal University of Technology, Niger State, Minna, Nigeria
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