Dynamic programming involves the use of recursive algorithms and optimal substructure to solve problems. In epidemiological models, this typically involves creating a system of subproblems that can be solved independently and then combined to form a solution to a larger problem. For example, in modeling disease spread, the progression of the disease can be broken down into stages such as exposure, infection, and recovery, each of which can be analyzed separately.
