  The capability of a network to cope with threats and survive attacks is
referred to as its robustness. This paper discusses one kind of robustness,
commonly denoted structural robustness, which increases when the spectral
radius of the adjacency matrix associated with the network decreases. We
discuss computational techniques for identifying edges, whose removal may
significantly reduce the spectral radius. Nonsymmetric adjacency matrices are
studied with the aid of their pseudospectra. In particular, we consider
nonsymmetric adjacency matrices that arise when people seek to avoid being
infected by Covid-19 by wearing facial masks of different qualities.
