  Identifying super-spreaders in epidemics is important to suppress the
spreading of disease especially when the medical resource is limited.In the
modern society, the information on epidemics transmits swiftly through various
communication channels which contributes much to the suppression of epidemics.
Here we study on the identification of super-spreaders in the
information-disease coupled spreading dynamics. Firstly, we find that the
centralities in physical contact layer are no longer effective to identify
super-spreaders in epidemics, which is due to the suppression effects from the
information spreading. Then by considering the structural and dynamical
couplings between the communication layer and physical contact layer, we
propose a centrality measure called coupling-sensitive centrality to identify
super-spreaders in disease spreading. Simulation results on synthesized and
real-world multiplex networks show that the proposed measure is not only much
more accurate than centralities on the single network, but also outperforms two
typical multilayer centralities in identifying super-spreaders. These findings
imply that considering the structural and dynamical couplings between layers is
very necessary in identifying the key roles in the coupled multilayer systems.
