We use a stochastic, agent-based simulation of the movements, activities, and social interactions of individuals in realistic synthetic populations to model the dynamics of the Influenza A (H1N1) virus as it spreads through the resulting contact network. In the simulation, the United States is stratified into 15 regions and the spatial and temporal dynamics of disease spread are presented. The results demonstrate a strong correlation between local demographic characteristics and pandemic severity, as evidenced by the rise of unanticipated spatial pandemic hotspots.
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