Predictive Analysis of COVID-19 Pandemic in India Based on SIR-F Model

Abstract Impact of COVID-19 has been devastating worldwide, it has disrupted lives of people, economy has fallen and millions of people have lost their jobs. Second peak of COVID-19 is making it even worse for many developing countries. In India, the second peak is reaching nearly 4 times the cases that were reported during the first peak, thus making it a challenge for the government to plan for the future without affecting the economy further. According to WHO, millions of enterprises are at existential threat, nearly half of the global workforce is at risk of losing their jobs and the entire food chain has been disrupted. In order to provide some assistance to the situation, this study aims to use the SIR-F Model, which is a variation of the SIR model. W. O. Kermack and A. G. McKendrick in 1927, proposed the model in which they classified a fixed population into three compartments: S(t), susceptible; I(t), Infected; R(t), Recovered. We have used the SIR-F model which differentiates between Recovered (meaning people infected and later recovered and thus now immune) and Fatality. We have simulated two scenarios including one in which we study the impact of medicine on future cases and also inspected various parameters which shed light on reasons behind increasing and decreasing the number of covid cases in India. In the future, this work can be extended further to develop a completely new model to consider those cases in which people have recovered but are still at a risk of reinfection.