  Interevent times in temporal contact data from humans and animals typically
obey heavy-tailed distributions, and this property impacts contagion and other
dynamical processes on networks. We theoretically show that distributions of
interevent times heavier-tailed than exponential distributions are a
consequence of the most basic metapopulation model used in epidemiology and
ecology, in which individuals move from a patch to another according to the
simple random walk. Our results hold true irrespectively of the network
structure and also for more realistic mobility rules such as high-order random
walks and the recurrent mobility patterns used for modeling human dynamics.
