  The SEIR model is a widely used epidemiological model used to predict the
rise in infections. This model has been widely used in different countries to
predict the number of Covid-19 cases. But the original SEIR model does not take
into account the effect of factors such as lockdowns, vaccines, and
re-infections. In India the first wave of Covid started in March 2020 and the
second wave in April 2021. In this paper, we modify the SEIR model equations to
model the effect of lockdowns and other influencers, and fit the model on data
of the daily Covid-19 infections in India using lmfit, a python library for
least squares minimization for curve fitting. We modify R0 parameter in the
standard SEIR model as a rectangle in order to account for the effect of
lockdowns. Our modified SEIR model accurately fits the available data of
infections.
