  The structure of complex networks has long been understood to play a role in
transmission and spreading phenomena on a graph. This behavior is difficult to
model analytically and is most often modeled numerically. Such networks form an
important part of the structure of society, including transportation networks.
As society fights to control the COVID-19 pandemic, an important question is to
choose the optimum balance between the full opening of transport networks and
the control of epidemic spread. In this paper we investigate how recent
advances in analyzing network structure using information theory could inform
decisions regarding the opening of such networks. By virtue of the richness of
data available we focus upon the worldwide airline network, but these methods
are in principle applicable to any transport network. We are able to
demonstrate that it is possible to substantially open the airline network and
have some degree of control on the spread of the virus.
