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Multiscale mobility networks and the large scale spreading of infectious diseases
Among the realistic ingredients to be considered in the computational
modeling of infectious diseases, human mobility represents a crucial challenge
both on the theoretical side and in view of the limited availability of
empirical data. In order to study the interplay between small-scale commuting
flows and long-range airline traffic in shaping the spatio-temporal pattern of
a global epidemic we i) analyze mobility data from 29 countries around the
world and find a gravity model able to provide a global description of
commuting patterns up to 300 kms; ii) integrate in a worldwide structured
metapopulation epidemic model a time-scale separation technique for evaluating
the force of infection due to multiscale mobility processes in the disease
dynamics. Commuting flows are found, on average, to be one order of magnitude
larger than airline flows. However, their introduction into the worldwide model
shows that the large scale pattern of the simulated epidemic exhibits only
small variations with respect to the baseline case where only airline traffic
is considered. The presence of short range mobility increases however the
synchronization of subpopulations in close proximity and affects the epidemic
behavior at the periphery of the airline transportation infrastructure. The
present approach outlines the possibility for the definition of layered
computational approaches where different modeling assumptions and granularities
can be used consistently in a unifying multi-scale framework.Comment: 10 pages, 4 figures, 1 tabl
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