  Computational models of infectious disease can be broadly categorized into
two types: individual-based (Agent-based), or compartmental models. While
compartmental models can be structured to separate distinct sectors of a
population, they are conceptually distinct from individual-based models in
which population structure emerges from micro-scale interactions. While the
conceptual distinction is straightforward, a fair comparison of the approaches
is difficult to achieve. Here, we carry out such a comparison by building a set
of compartmental metapopulation models from an agent-based representation of a
real population. By adjusting the compartmental model to approximately match
the dynamics of the Agent-based model, we identify two key qualitative
properties of the individual-based dynamics which are lost upon aggregation
into metapopulations. These are (1) the local depletion of susceptibility to
infection, and (2) decoupling of different regional groups due to correlation
between commuting behaviors and contact rates. The first of these effects is a
general consequence of aggregating small, closely connected groups (i.e.,
families) into larger homogeneous metapopulations. The second can be
interpreted as a consequence of aggregating two distinct types of individuals:
school children, who travel short distances but have many potentially
infectious contacts, and adults, who travel further but tend to have fewer
contacts capable of transmitting infection. Our results could be generalised to
other types of correlations between the characteristics of individuals and the
behaviors that distinguish them.
