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COVID-19 is a novel virus that has spread globally, and governments around the world often implement different strategies to prevent its spread. In the literature, several COVID-19 models have been studied with the bilinear incident rate. In this study, the S1V1E1I1Q1R1 (susceptible-vaccinated-exposed-infective-quarantined-recovered) COVID-19 model is proposed. To investigate how the disease spreads in the population, an algorithm is used. The efficacy of the algorithm is used to calculate the disease-free equilibrium point. A next generation matrix technique is used to find R0. Furthermore, to check the effect of parameters on the basic reproduction number (R0), the sensitivity analysis is conducted. Numerical simulation displays that the disease spreads in the population by increasing the value of the contact rate β while the disease spread in the population reduces by increasing the value of the vaccination rate θ, quarantine rate ϕ, and recovery rate γ. Different optimal control strategies, such as social distance and quick isolation, are also implemented.
Shah et al. (2024) studied this question.
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