  The reversible spreading processes with repeated infection widely exist in
nature and human society, such as gonorrhea propagation and meme spreading.
Identifying influential spreaders is an important issue in the reversible
spreading dynamics on complex networks, which has been given much attention.
Except for structural centrality, the nodes' dynamical states play a
significant role in their spreading influence in the reversible spreading
processes. By integrating the number of outgoing edges and infection risks of
node's neighbors into structural centrality, a new measure for identifying
influential spreaders is articulated which considers the relative importance of
structure and dynamics on node influence. The number of outgoing edges and
infection risks of neighbors represent the positive effect of the local
structural characteristic and the negative effect of the dynamical states of
nodes in identifying influential spreaders, respectively. We find that an
appropriate combination of these two characteristics can greatly improve the
accuracy of the proposed measure in identifying the most influential spreaders.
Notably, compared with the positive effect of the local structural
characteristic, slightly weakening the negative effect of dynamical states of
nodes can make the proposed measure play the best performance. Quantitatively
understanding the relative importance of structure and dynamics on node
influence provides a significant insight into identifying influential nodes in
the reversible spreading processes.
