Modelling India's Second Covid Wave Based on Human Social Behaviour and Creating the SVIR Model

Abstract

The Covid-19 pandemic has affected more than 150 million people around the world. India has been hit particularly hard, especially the second wave from March 2021 till present(May 2021). The current model used for prediction of covid transmission is the susceptible-recovered-infected(SIR) model, however it is unable to model real life social scenarios which have major impact on the spread of contagious diseases. Research has already linked a higher transmission rates in countries with a denser population, however this paper focuses on changing density due to social scenarios in the same region to estimate the impact of human behaviour. We combine Covid-19 data with human social behaviour to create a modified model specific to India, using regression to calculate the contact rate.Making it a function of density, we estimate how far super spreader events conducted in India such as the kumbh mela and political rallies contributed to the second wave. We then model future trends, exploring how human behaviour will change the trajectory of the second wave and why a nationwide lockdown is absolutely critical, given not just the sheer number of cases, but also slow vaccination rates, overcrowding of hospitals and the ongoing oxygen crisis. We forecast number of Covid cases in the future in three different situations, a super spreader event is conducted, nothing changes, and a nation-wide lockdown, discovering that contact rate should be modelled as a function of density and human social behaviour should explicitly be used in transmission models that predict the impact of Covid19. We also factor in vaccination rates creating the SVIR model, evaluating the impact of vaccine roll out as compared to lock downs, concluding the social distancing and covid precautions will need to be continued until at least triple of India's current daily vaccine roll out is achieved, which will flatten the curve by reducing the number of susceptible people significantly.