Before revision: Building on the observation that the spread of an infection is subject to stochastic fluctuations when infection numbers are small, we propose a strategy of containment that falls in between relatively mild social distancing measures and maximally restrictive lockdown strategies. The key innovation of our proposed strategy is its ability to recruit stochastic effects such as spontaneous extinction and fluctuations in timing to contain the epidemic , even when infection numbers in the population as a whole are not small and their spatial distribution is unknown.
After revision: 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 infection numbers in the population as a whole are not small and their spatial distribution is unknown.