Inverse Optimal Impulsive Control for a SIR Epidemic Model

Epidemiological models constitute a fundamental means to understand the behavior and evolution of infectious diseases, as well as the mechanisms of action to counteract them. If an infectious disease spreads rapidly and affects a big population, it is vital to have effective control schemes that optimize the amount of available resources to mitigate the propagation of the disease, before it becomes a risk condition for public health systems. Inspired by this idea, we consider an extension of the SIR epidemic model and study the application of an impulsive control action to this system that minimizes vaccines and treatment given to population, using an inverse optimal control (IOC) approach.