id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-243070-0b06zk1q	Lesniewski, Andrew	Epidemic control via stochastic optimal control	2020-04-14		.txt	text/plain	3793	295	63	This results in a system of forward backward stochastic differential equations, which is amenable to numerical solution via Monte Carlo simulations. In this note we study the problem of optimal control of an epidemic modeled by means of a stochastic extension of the SIR model (see Section 2 for definition). The optimal control problem is recast as the stochastic minimum principle problem and formulated in terms of a system of forward backward stochastic differential equations (FBSDE). If a vaccine against the disease is unavailable, we set u 1 = 0 in the equation above, which yields the following controlled process: Using Ito's lemma, we verify that these two conditions lead to the following nonlinear partial differential equation for the value function, namely the stochastic Hamilton-Jacobi-Bellman equation: Under this running cost function, the optimal policy is to implement a draconian isolation regime, which leads to a rapid drop in infections, while keeping the susceptible fraction of the population at a very high level.	./cache/cord-243070-0b06zk1q.txt	./txt/cord-243070-0b06zk1q.txt