  Spreading dynamics has been considered to take place in temporal networks,
where temporal interaction patterns between nodes show non-Poissonian bursty
nature. The effects of inhomogeneous interevent times (IETs) on the spreading
have been extensively studied in recent years, yet little is known about the
effects of correlations between IETs on the spreading. In order to investigate
those effects, we study two-step deterministic susceptible-infected (SI) and
probabilistic SI dynamics when the interaction patterns are modeled by
inhomogeneous and correlated IETs, i.e., correlated bursts. By analyzing the
transmission time statistics in a single-link setup and by simulating the
spreading in Bethe lattices and random graphs, we conclude that the positive
correlation between IETs slows down the spreading. We also argue that the
shortest transmission time from one infected node to its susceptible neighbors
can successfully explain our numerical results.
