Abstract
Purpose The purpose of this study is to obtain an analytical solution for a nonlinear system of the COVID-19 model for susceptible, exposed, infected, isolated and recovered. Design/methodology/approach The Laplace decomposition method and the differential transformation method are used. Findings The obtained analytical results are useful on two fronts: first, they would contribute to a better understanding of the dynamic spread of the COVID-19 disease and help prepare effective measures for prevention and control. Second, researchers would benefit from these results in modifying the model to study the effect of other parameters such as partial closure, awareness and vaccination of isolated groups on controlling the pandemic. Originality/value The approach presented is novel in its implementation of the nonlinear system of the COVID-19 model
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