  During the Covid-19 pandemic, most governments across the world imposed
policies like lock-down of public spaces and restrictions on people's movements
to minimize the spread of the virus through physical contact. However, such
policies have grave social and economic costs, and so it is important to
pre-assess their impacts. In this work we aim to visualize the dynamics of the
pandemic in a city under different intervention policies, by simulating the
behavior of the residents. We develop a very detailed agent-based model for a
city, including its residents, physical and social spaces like homes,
marketplaces, workplaces, schools/colleges etc. We parameterize our model for
Kolkata city in India using ward-level demographic and civic data. We
demonstrate that under appropriate choice of parameters, our model is able to
reproduce the observed dynamics of the Covid-19 pandemic in Kolkata, and also
indicate the counter-factual outcomes of alternative intervention policies.
