Anecdotal evidence about human travel is plentiful. But quantifying human movement and dispersal, and then applying general principles to those data, is not straightforward. Elsewhere in this issue, a group of theoretical physicists describe how they have taken an ingenious approach to the problem (D. Brockmann et al. Nature 439, 462–465; 2006). They use the dispersal of dollar bills within the United States as a proxy measurement for human movement.

The researchers analysed data on the peregrinations of more than half-a-million US dollar bills recorded over a five-year period on an online bill-tracking system ( This allowed them to quantify even statistically rare events with high reliability. They found that the movement of dollar bills resembles enhanced diffusion, or ‘superdiffusion’. Long-distance jumps are disproportionately important in the distribution of travelling distances. And this distribution decays as a power law reminiscent of ‘Lévy flights’, which are characterized by many short steps interspersed with long-distance jumps.

The result may seem unsurprising — most cash transactions are carried out locally, but every now and again someone departs and uses the bill at a distant location. The beauty is that actual numbers can now be put on the process.


Although the observed distribution of travelling distances implies superdiffusion, however, this process is attenuated by the tendency of bills to remain in the same area for longer than might be expected given the overall pattern of movement. Thus, human travelling behaviour apparently involves disproportionately long waiting times between displacements as well as jumps without any characteristic distance scale.

But how well do bill trajectories reflect actual human movement? Happily, the authors find that data on passenger travel on the US aviation network, and long-distance human travel information published by the US Bureau of Transportation Statistics, agree well with the results based on dollar-bill trajectories.

This research is more than a curiosity — epidemiologists could in principle use quantitative information on human movement to understand better how infectious diseases such as influenza spread.