  The main goal of this paper is to model the epidemic and flattening the
infection curve of the social networks. Flattening the infection curve implies
slowing down the spread of the disease and reducing the infection rate via
social-distancing, isolation (quarantine) and vaccination. The
nan-pharmaceutical methods are a much simpler and efficient way to control the
spread of epidemic and infection rate. By specifying a target group with high
centrality for isolation and quarantine one can reach a much flatter infection
curve (related to Corona for example) without adding extra costs to health
services. The aim of this research is, first, modeling the epidemic and, then,
giving strategies and structural algorithms for targeted vaccination or
targeted non-pharmaceutical methods for reducing the peak of the viral disease
and flattening the infection curve. These methods are more efficient for
nan-pharmaceutical interventions as finding the target quarantine group
flattens the infection curve much easier. For this purpose, a few number of
particular nodes with high centrality are isolated and the infection curve is
analyzed. Our research shows meaningful results for flattening the infection
curve only by isolating a few number of targeted nodes in the social network.
The proposed methods are independent of the type of the disease and are
effective for any viral disease, e.g., Covid-19.
