Before revision:  Building on the key observation that the stochastic evolution of a process such as the spread of infection has a finite extinction probability even when it is expected to grow exponentially on average , we propose a strategy of containment that falls in between the relatively mild social distancing measures and the maximally restrictive lock-down strategies. Our proposed strategy involves partitioning the population into smaller isolated sub-populations within which, while social distancing is practised as much as possible to reduce the contact rate, a relatively normal lifestyle is maintained.
After revision:  Building on the key observation that the stochastic evolution of a process such as the spread of infection has a finite extinction probability even when it is expected to grow exponentially on average , we propose a strategy of containment that falls in between the 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. It involves partitioning the population into smaller isolated sub-populations within which, while social distancing is practised as much as possible to reduce the contact rate, a relatively normal lifestyle is maintained.