  Global mobility flow data are at the heart of spatial epidemiological models
used to predict infectious disease behavior but this wealth of data on human
mobility has been largely neglected by reconstructions of pathogen evolutionary
dynamics using viral genetic data. Although stochastic models of viral
evolution may potentially be informed by such data, a major challenge lies in
deciding which mobility processes are critical and to what extent they
contribute to shaping contemporaneous distributions of pathogen diversity.
Here, we develop a framework to integrate predictors of viral diffusion with
phylogeographic inference and estimate human influenza H3N2 migration history
while simultaneously testing and quantifying the factors that underly it. We
provide evidence for air travel governing the global dynamics of human
influenza whereas other processes act at a more local scale.
