Analysis of the Adomian decomposition method to estimate the COVID-19 pandemic

Several techniques, including mathematical models, have been explored since the onset of COVID-19 transmission to evaluate the end outcome and implement drastic measures for this illness. Using the currently infected, noninfected, exposed, susceptible, and recovered cases in the Indian community, we created a mathematical model to describe the transmission of COVID-19. In particular, we used the semianalytical Adomian decomposition method without considering any discretization to perform the first-order differential equations related to COVID-19 cases. According to our early findings, rigorous initial isolation for 22–25 days would reduce the number of exposed and newly infected people. As a result of the downstream effect, the number of suspected and recovered persons would remain stable, assuming that social distance is properly recognized. In a larger sense, the parameters established by our mathematical model may aid in the refinement of future pandemic tactics.