Study of COVID-19 growth and decay cases through mathematical models

In this article we proved various results by using Epidemic model, Linear growth model and Effects of immigration in context of Covid-19 pandemic. By using first order differential equations we studied the Epidemic model, we found that, if we will not take care of SOP measures provided by the Government, then all the susceptible i.e. prone to disease become infected to Covid +ve. Through Linear growth model, we found the result x^*(t) = ce^at which states that, if a > 0, then the population of Covid patient will become double of its present size at time T, x^*(t) = ce^at. If a < 0, then the population of Covid patient will become half of its present size in time T. Also we concluded that, if there is immigration into the population size from outside and if we follow SOP measures provided by government, then the rate is directly proportional to the population of Covid infected per case. The results of models ensure and make us aware to follow standard operating procedure (SOP) measures provided by the Government in the view of Covid-19. The study of model provides better understanding of the challenges faced and curb the disease.