Analysis of optimal confinement policies of epidemic models with vaccinations

L. Belasko Garate, J. Doncel

We analyze a variant of the SIR model where susceptible population can avoid to get the infection and become recovered with a vaccine. We consider that the susceptible population can be protected from the epidemic following some confinement policy. We assume that the infected population incurs a cost and that the cost of confinement decreases with the susceptible population's exposure level.
We aim to analyze the optimal confinement policy in this context. We first model this problem as a Markov Decision Process with infinite horizon and discounted cost and we show that the optimal confinement strategy is of threshold-type. We also tackle this problem from the perspective of Reinforcement Learning, where no information about the dynamics of the systems and the costs of the population is known.

Keywords: Markov Decision Process, SIR model, Reinforcement Learning

Stochastic processes and their applications I
June 13, 2025  11:00 AM
Auditorio 2. Leandre Cristòfol

M. GONZALEZ BERNAL, R. E. Lillo, P. Ramirez Cobo

J. Baz González

M. Alcalde, M. Lafuente, F. J. López, G. Sanz

P. Martín Chávez, I. del Puerto, M. González Velasco