Jiacheng Chen, Kexin Feng, Lorenzo Freddi, Dan Goreac, Juan Li
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Optimality of Vaccination for Prevalence-Constrained SIRS Epidemics
The aim of the present paper is to investigate the optimal vaccination policies with prevalence restrictions in an SIRS demographic model. We provide a well-posedness result for the system and give a thorough description of safety zones (immunity and feasible) when intensive care units (ICU) restrictions are enforced on the prevalence. Using Pontryagin’s principle for state-constrained dynamics we show that the optimal vaccination policy is of bang–bang type and give further specifics on the precise structure. The paper is intended as a counter-part to Avram et al. (Appl Math Comput 418:126816, 2022) where non-pharmaceutical interventions have been considered.
期刊介绍:
The Applied Mathematics and Optimization Journal covers a broad range of mathematical methods in particular those that bridge with optimization and have some connection with applications. Core topics include calculus of variations, partial differential equations, stochastic control, optimization of deterministic or stochastic systems in discrete or continuous time, homogenization, control theory, mean field games, dynamic games and optimal transport. Algorithmic, data analytic, machine learning and numerical methods which support the modeling and analysis of optimization problems are encouraged. Of great interest are papers which show some novel idea in either the theory or model which include some connection with potential applications in science and engineering.