Asymptotics; Belgium; Case-studies; Early disease; Formal proofs; Model-predictive control; Model-predictive control approach; Operational constraints; Predictive control strategy; Vaccination strategy; Control and Systems Engineering; Industrial and Manufacturing Engineering; Control and Optimization; Modeling and Simulation
Abstract :
[en] This work proposes a Model Predictive Control (MPC) approach for epidemic containment, using COVID-19 in Wallonia, Belgium, as a case study. The proposed framework presents an optimal age-structured vaccination strategy that aims to minimize fatalities, promote early disease eradication, and adhere to operational constraints. By incorporating an age-structured Susceptible-Infected-Recovered-Deceased model with an explicit vaccination term, the MPC strategy adapts dynamically to the evolving epidemic states. Formal proofs of asymptotic stability and recursive feasibility of the proposed MPC algorithm are provided.
Computational resources have been provided by the Consortium des Equipements de Calcul Intensif (CECI), funded by the Fonds de la Recherche Scientifique de Belgique (F.R.S.-FNRS) under Grant No. 2.5020.11 and by the Walloon Region. The AVIQ, l Agence Wallonne pour la Sante, la Protection sociale, le Handicap et les Familles has given access to valuable data for the calibration of the parameters.
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