  Human mobility is a key factor in spatial disease dynamics and related
phenomena. In computational models host mobility is typically modelled by
diffusion in space or on metapolulation networks. Alternatively, an effective
force of infection across distance has been introduced to capture spatial
dispersal implicitly. Both approaches do not account for important aspects of
natural human mobility, diffusion does not capture the high degree of
predictability in natural human mobility patters, e.g. the high percentage of
return movements to individuals' base location, the effective force of
infection approach assumes immediate equilibrium with respect to dispersal.
These conditions are typically not met in natural scenarios. We investigate an
epidemiological model that explicitly captures natural individual mobility
patterns. We systematically investigate generic dynamical features of the model
on regular lattices as well as metapopulation networks and show that generally
the model exhibits significant dynamical differences in comparison to ordinary
diffusion and effective force of infection models. For instance, the natural
human mobility model exhibits a saturation of wave front speeds and a novel
type of invasion threshold that is a function of the return rate in mobility
patterns. In the light of these new findings and with the availability of
precise and pervasive data on human mobility our approach provides a framework
for a more sophisticated modeling of spatial disease dynamics.
