  The networked structure of contacts shapes the spreading of epidemic
processes. Recent advances on network theory have improved our understanding of
the epidemic processes at large scale. The relevance of several considerations
still needs to be evaluated in the study of epidemic spreading. One of them is
that of accounting for the influence of origin and destination patterns in the
flow of the carriers of an epidemic. Here we compute origin-destination
patterns compatible with empirical data of coarse grained flows in the air
transportation network. We study the incidence of epidemic processes in a
metapopulation approach considering different alternatives to the flows prior
knowledge. The data-driven scenario where the estimation of origin and
destination flows is considered turns out to be relevant to assess the impact
of the epidemics at a microscopic level (in our scenario, which populations are
infected). However, this information is irrelevant to assess its macroscopic
incidence (fraction of infected populations). These results are of interest to
implement even better computational platforms to forecast epidemic incidence.

Physics and Society;Statistical Mechanics;Social and Information Networks