Prediction and predictability of global epidemics: the role of the airline transportation network

The systematic study of large-scale networks has unveiled the ubiquitous presence of connectivity patterns characterized by large scale hetero geneities and unbounded statistical fluctuations. These features affect dramatically the be havior 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 stochasticit y of disease transmission and traffic flows. In order to address these issues we define a set of novel q uantitative measures able to characterize the level of heterogeneity and predictabil ity of the epidemic pattern. These