Model predictive control for optimal social distancing in a type SIR-switched model

SERENO, JUAN; D'JORGE, AGUSTINA; FERRAMOSCA, ANTONIO; HERNANDEZ VARGAS, ESTEBAN ABELARDO; GONZÁLEZ, ALEJANDRO HERNÁN

Ghent

Conferencia; 11th IFAC Biological and Medical Systems 2021; 2021

International Federation of Automatic Control IFAC

Social distancing strategies have been adopted bygovernments to manage the COVID-19 pandemic, since the firstoutbreak began. However, further epidemic waves keep out thereturn of economic and social activities to their standard levels ofintensity. Social distancing interventions based on control theoryare needed to consider a formal dynamic characterization ofthe implemented SIR-type model to avoid unrealistic objectivesand prevent further outbreaks. The objective of this work istwofold: to fully understand some dynamical aspects of SIR-typemodels under control actions (associated with second waves) and,based on it, to propose a switching non-linear model predictivecontrol that optimize the non-pharmaceutical measures strategy.Opposite to other strategies, the objective here is not just tominimize the number of infected individuals at any time, butto minimize the final size of the epidemic while minimizing thetime of social restrictions and avoiding the infected prevalencepeak to overpass a maximum established by the healthcare systemcapacity. Simulations illustrate the benefits of the aforementionedproposal.