On the Robustness of In- and Out-Components in a Temporal Network

Abstract

We find a ranking of nodes according to their component sizes reasonably stable for a wide range of infectious periods. Samples based on this ranking are robust enough against varying disease parameters and hence are promising tools for disease control.