  The first mitigation response to the Covid-19 pandemic was to limit
person-to-person interaction as much as possible. This was implemented by the
temporary closing of many workplaces and people were required to follow social
distancing. Networks are a great way to represent interactions among people and
the temporary severing of these interactions. Here, we present a network model
of human-human interactions that could be mediators of disease spread. The
nodes of this network are individuals and different types of edges denote
family cliques, workplace interactions, interactions arising from essential
needs, and social interactions. Each individual can be in one of four states:
susceptible, infected, immune, and dead. The network and the disease parameters
are informed by the existing literature on Covid-19. Using this model, we
simulate the spread of an infectious disease in the presence of various
mitigation scenarios. For example, lockdown is implemented by deleting edges
that denote non-essential interactions. We validate the simulation results with
the real data by matching the basic and effective reproduction numbers during
different phases of the spread. We also simulate different possibilities of the
slow lifting of the lockdown by varying the transmission rate as facilities are
slowly opened but people follow prevention measures like wearing masks etc. We
make predictions on the probability and intensity of a second wave of infection
in each of these scenarios.
