  The systematic study of large-scale networks has unveiled the ubiquitous
presence of connectivity patterns characterized by large scale heterogeneities
and unbounded statistical fluctuations. These features affect dramatically the
behavior of the diffusion processes occurring on networks, determining the
ensuing statistical properties of their evolution pattern and dynamics. In this
paper, we investigate the role of the large scale properties of the airline
transportation network in determining the global evolution of emerging disease.
We present a stochastic computational framework for the forecast of global
epidemics that considers the complete world-wide air travel infrastructure
complemented with census population data. We address two basic issues in global
epidemic modeling: i) We study the role of the large scale properties of the
airline transportation network in determining the global diffusion pattern of
emerging diseases; ii) We evaluate the reliability of forecasts and outbreak
scenarios with respect to the intrinsic stochasticity of disease transmission
and traffic flows. In order to address these issues we define a set of novel
quantitative measures able to characterize the level of heterogeneity and
predictability of the epidemic pattern. These measures may be used for the
analysis of containment policies and epidemic risk assessment.
