Transport and Optimal Control of Vaccination Dynamics for COVID-19
Mohamed Abdelaziz Zaitri, Mohand Ouamer Bibi, Delfim F. M. Torres
TL;DR
This paper presents a mathematical model combining heat diffusion and SEIR dynamics to optimize COVID-19 vaccination strategies, using control theory and simulations to evaluate effectiveness in Italy.
Contribution
It introduces a novel integrated model for vaccine transfer and epidemic control, applying optimal control to improve vaccination strategies.
Findings
Vaccination significantly reduces COVID-19 spread in simulations.
Optimal control improves vaccination timing and distribution.
Model predicts epidemic dynamics with and without vaccination.
Abstract
We develop a mathematical model for transferring the vaccine BNT162b2 based on the heat diffusion equation. Then, we apply optimal control theory to the proposed generalized SEIR model. We introduce vaccination for the susceptible population to control the spread of the COVID-19 epidemic. For this, we use the Pontryagin minimum principle to find the necessary optimality conditions for the optimal control. The optimal control problem and the heat diffusion equation are solved numerically. Finally, several simulations are done to study and predict the spread of the COVID-19 epidemic in Italy. In particular, we compare the model in the presence and absence of vaccination.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.