  The infectious diseases are spreading due to human interactions enabled by
various social networks. Therefore, when a new pathogen such as SARS-CoV-2
causes an outbreak, the non-pharmaceutical isolation strategies (e.g., social
distancing) are the only possible response to disrupt its spreading. To this
end, we introduce the new epidemic model (SICARS) and compare the centralized
(C), decentralized (D), and combined (C+D) social distancing strategies, and
analyze their efficiency to control the dynamics of COVID-19 on heterogeneous
complex networks. Our analysis shows that the centralized social distancing is
necessary to minimize the pandemic spreading. The decentralized strategy is
insufficient when used alone, but offers the best results when combined with
the centralized one. Indeed, the (C+D) is the most efficient isolation strategy
at mitigating the network superspreaders and reducing the highest node degrees
to less than 10% of their initial values. Our results also indicate that
stronger social distancing, e.g., cutting 75% of social ties, can reduce the
outbreak by 75% for the C isolation, by 33% for the D isolation, and by 87% for
the (C+D) isolation strategy. Finally, we study the impact of proactive versus
reactive isolation strategies, as well as their delayed enforcement. We find
that the reactive response to the pandemic is less efficient, and delaying the
adoption of isolation measures by over one month (since the outbreak onset in a
region) can have alarming effects; thus, our study contributes to an
understanding of the COVID-19 pandemic both in space and time. We believe our
investigations have a high social relevance as they provide insights into
understanding how different degrees of social distancing can reduce the peak
infection ratio substantially; this can make the COVID-19 pandemic easier to
understand and control over an extended period of time.
