  Using a stochastic Susceptible-Infected-Removed (SIR) meta-population model
of disease transmission, we present analytical calculations and numerical
simulations dissecting the interplay between stochasticity and the division of
a population into mutually independent sub-populations. We show that
subdivision activates two stochastic effects---extinction and
desynchronization---diminishing the overall impact of the outbreak, even when
the total population has already left the stochastic regime and the basic
reproduction number is not altered by the subdivision. Both effects are
quantitatively captured by our theoretical estimates, allowing us to determine
their individual contributions to the observed reduction of the peak of the
epidemic.
