  In this paper we propose a method for sparse dynamic allocation of resources
to bound the risk of spreading processes, such as epidemics and wildfires,
using convex optimization and dynamic programming techniques. Here, risk is
defined as the risk of an outbreak, i.e. the product of the probability of an
outbreak occurring over a time interval and the future impact of that outbreak,
and we can allocate budgeted resources each time step to bound or minimize the
risk. Our method in particular provides sparsity of resources, which is
important due to the large network structures involved with spreading processes
and has advantages when resources can not be distributed widely.
