Determining the pandemic potential of an emerging infectious disease and how it depends on the
various epidemic and population aspects is critical for the preparation of an adequate response aimed
at its control. The complex interplay between population movements in space and non-homogeneous
mixing patterns have so far hindered the fundamental understanding of the conditions for spatial
invasion through a general theoretical framework. To address this issue, we present an analytical
modelling approach taking into account such interplay under general conditions of mobility and
interactions, in the simplifying assumption of two population classes.
We describe a spatially structured population with non-homogeneous mixing and travel behaviour
through a multi-host stochastic epidemic metapopulation model. Different population partitions,
mixing patterns and mobility structures are considered, along with a specific application for the study
of the role of age partition in the early spread of the 2009 H1N1 pandemic influenza.
We provide a complete mathematical formulation of the model and derive a semi-analytical
expression of the threshold condition for global invasion of an emerging infectious disease in the
metapopulation system. A rich solution space is found that depends on the social partition of the
population, the pattern of contacts across groups and their relative social activity, the travel attitude
of each class, and the topological and traffic features of the mobility network. Reducing the activity
of the less social group and reducing the cross-group mixing are predicted to be the most efficient
strategies for controlling the pandemic potential in the case the less active group constitutes the
majority of travellers. If instead traveling is dominated by the more social class, our model predicts
the existence of an optimal across-groups mixing that maximises the pandemic potential of the
disease, whereas the impact of variations in the activity of each group is less important.
The proposed modelling approach introduces a theoretical framework for the study of infectious
diseases spread in a population with two layers of heterogeneity relevant for the local transmission
and the spatial propagation of the disease. It can be used for pandemic preparedness studies to
identify adequate interventions and quantitatively estimate the corresponding required effort, as well
as in an emerging epidemic situation to assess the pandemic potential of the pathogen from
population and early outbreak data.