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- Given the serious consequences that an epidemic may have, it is essential to control its spread through several interventions such as social distancing, lockdown or vaccination. However, these interventions have a cost and they have to be implemented properly to be effective. The challenge of managing epidemics is therefore to limit their spread as much as possible while minimizing the cost of the interventions implemented. This master thesis addresses several questions of epidemic management in the context of the COVID-19 outbreak in Belgium. The main questions considered in this work are: For each week of a one-year horizon, what is the optimal transmission rate of the disease to minimize its spread and the cost of the health measures implemented to achieve such a rate? Should health measures be different for the vulnerable and the non-vulnerable population? Who should be vaccinated first between the vulnerable population, the non-vulnerable population and the health care workers? To answer these questions, we use a control approach. Indeed, we design optimal control problems and model predictive control problems to find the optimal intervention strategies in order to curtail the spread of the disease while minimizing the cost of the interventions.
Citations
Doumont, M. (2022). Model predictive and optimal control for epidemic management. https://dial-mem.test.bib.ucl.ac.be/handle/2078.2/28285