An Analysis on Infected Cases of Corona Virus Using Scientific Computing Methods

The Corona Virus disease is a worldwide health care issue, and international efforts to manage it have been suggested and discussed. Despite the fact that numerous studies have been done using clinical data and documented infected cases, there is always need for more study since a lot of complex factors are involved in future prediction. As a result, mathematical modeling is an essential tool for estimating critical transmission parameters and forecasting disease model dynamics. We analyze and offer various models for the Corona Virusin this study, which can answer significant concerns regarding global health care and provide crucial suggestions. Euler's method, Runge–Kutta method of order two (RK2) are two well-known numerical approaches for solving such problems. The results, which are based on the numerical approaches provide approximate solutions, provide critical answers to this worldwide challenge. The number of infected, recovered, and quarantined persons in the future can be estimated using numerical findings. The findings might also support worldwide efforts to develop more preventions and enhance intermediation programs. The proposed model can be refereed to be a realistic description of this pandemic.