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Epidemic containment is a major concern when confronting large-scaleinfections in complex networks. Many works have been devoted to analyticallyunderstand how to restructure the network to minimize the impact of majoroutbreaks of infections at large scale. In many cases, the strategies consistin the isolation of certain nodes, while less attention has been paid to theintervention on links. In epidemic spreading, links inform about theprobability of carrying the contagion of the disease from infected tosusceptible individuals. Note that these states depend on the full structure ofthe network, and its determination is not straightforward from the knowledge ofnodes' states. Here, we confront this challenge and propose a set ofdiscrete-time governing equations \rev{which} can be closed and analyzed,assessing the contribution of links to spreading processes in complex networks.Our approach allows a scheme for the \rev{containment} of epidemics, based ondeactivating the most important links in transmitting the disease. The model isvalidated in synthetic and real networks, obtaining an accurate determinationof the epidemic incidence and the critical thresholds. Epidemic containmentbased on links' deactivation promises to be an effective tool to maintainfunctionality on networks while controlling the spread of diseases, as forexample in air transportation networks.

Effective approach to epidemic containment using link equations in complex networks