  The study of complex networks sheds light on the relation between the
structure and function of complex systems. One remarkable result is the absence
of an epidemic threshold in infinite-size scale-free networks, which implies
that any infection will perpetually propagate regardless of the spreading rate.
The vast majority of current theoretical approaches assumes that infections are
transmitted as a reaction process from nodes to all neighbors. Here we adopt a
different perspective and show that the epidemic incidence is shaped by traffic
flow conditions. Specifically, we consider the scenario in which epidemic
pathways are defined and driven by flows. Through extensive numerical
simulations and theoretical predictions, it is shown that the value of the
epidemic threshold in scale-free networks depends directly on flow conditions,
in particular on the first and second moments of the betweenness distribution
given a routing protocol. We consider the scenarios in which the delivery
capability of the nodes is bounded or unbounded. In both cases, the threshold
values depend on the traffic and decrease as flow increases. Bounded delivery
provokes the emergence of congestion, slowing down the spreading of the disease
and setting a limit for the epidemic incidence. Our results provide a general
conceptual framework to understand spreading processes on complex networks.
