  To contain the propagation of emerging diseases that are transmissible from
human to human, non-pharmaceutical interventions (NPIs) aimed at reducing the
interactions between humans are usually implemented. One example of the latter
kind of measures is social distancing, which can be either policy-driven or can
arise endogenously in the population as a consequence of the fear of infection.
However, if NPIs are lifted before the population reaches herd immunity,
further re-introductions of the pathogen would lead to secondary infections.
Here we study the effects of different social distancing schemes on the large
scale spreading of diseases. Specifically, we generalize metapopulation models
to include social distancing mechanisms at the subpopulation level and model
short- and long-term strategies that are fed with local or global information
about the epidemics. We show that different model ingredients might lead to
very diverse outcomes in different subpopulations. Our results suggest that
there is not a unique answer to the question of whether contention measures are
more efficient if implemented and managed locally or globally and that model
outcomes depends on how the full complexity of human interactions is taken into
account.
