Networks which trace the activities and interactions of individuals, transportation fluxes and population movements on local and global scale have been analyzed and found to exhibit large scale heterogeneity, self-organization and other properties typical of complex systems. Here we analyze the impact of mobility networks on the global spreading of emerging infectious diseases. We define a computational model for the large scale spread of infectious diseases that integrates the air transportation network with demographic data.
The model is used to study the specific case of the SARS epidemic and to provide scenario forecasts for pandemic influenza. The effect of the network complexity on the predictability of the global spreading pattern of emerging diseases is analyzed.
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