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This content will become publicly available on January 1, 2023

Title: Optimization of vaccination for COVID-19 in the midst of a pandemic

During the Covid-19 pandemic a key role is played by vaccination to combat the virus. There are many possible policies for prioritizing vaccines, and different criteria for optimization: minimize death, time to herd immunity, functioning of the health system. Using an age-structured population compartmental finite-dimensional optimal control model, our results suggest that the eldest to youngest vaccination policy is optimal to minimize deaths. Our model includes the possible infection of vaccinated populations. We apply our model to real-life data from the US Census for New Jersey and Florida, which have a significantly different population structure. We also provide various estimates of the number of lives saved by optimizing the vaccine schedule and compared to no vaccination.

Authors:
; ; ; ; ; ; ; ;
Award ID(s):
2018873
Publication Date:
NSF-PAR ID:
10336887
Journal Name:
Networks and Heterogeneous Media
Volume:
17
Issue:
3
Page Range or eLocation-ID:
443
ISSN:
1556-1801
Sponsoring Org:
National Science Foundation
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