OPTIMIZATION OF VACCINATION FOR COVID-19 IN THE MIDST OF A PANDEMIC

Qi Luo; Ryan Weightman; Sean T. McQuade; Mateo Diaz; Emmanuel Trelat; William Barbour; Dan Work; Samitha Samaranayake; Benedetto Piccoli

doi:10.3934/nhm.2022016

Back

OPTIMIZATION OF VACCINATION FOR COVID-19 IN THE MIDST OF A PANDEMIC

Journal article

Peer reviewed

OPTIMIZATION OF VACCINATION FOR COVID-19 IN THE MIDST OF A PANDEMIC

Qi Luo, Ryan Weightman, Sean T. McQuade, Mateo Diaz, Emmanuel Trelat, William Barbour, Dan Work, Samitha Samaranayake and Benedetto Piccoli

Networks and heterogeneous media, Vol.17(3), pp.443-466

06/01/2022

DOI: 10.3934/nhm.2022016

Files and links (1)

url

https://doi.org/10.3934/nhm.2022016View

Published (Version of record) Open Access

Abstract

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.

Mathematics

Mathematics, Interdisciplinary Applications

Physical Sciences

Science & Technology

Details

Title: Subtitle: OPTIMIZATION OF VACCINATION FOR COVID-19 IN THE MIDST OF A PANDEMIC
Creators: Qi Luo - Clemson University
Ryan Weightman - Rutgers Camden, Ctr Computat & Integrat Biol, Camden, NJ USA
Sean T. McQuade - Rutgers Camden, Ctr Computat & Integrat Biol, Camden, NJ USA
Mateo Diaz - California Institute of Technology
Emmanuel Trelat - Laboratoire Jacques-Louis Lions
William Barbour - Vanderbilt University
Dan Work - Vanderbilt University
Samitha Samaranayake - Cornell University
Benedetto Piccoli - Rutgers Camden, Ctr Computat & Integrat Biol, Math, Camden, NJ USA
Resource Type: Journal article
Publication Details: Networks and heterogeneous media, Vol.17(3), pp.443-466
Publisher: Amer Inst Mathematical Sciences-Aims
DOI: 10.3934/nhm.2022016
ISSN: 1556-1801
eISSN: 1556-181X
Number of pages: 24
Grant note: Joseph and Loretta Lopez Chair endowment 2033580 / NSF CMMI project
Language: English
Date published: 06/01/2022
Academic Unit: Business Analytics
Record Identifier: 9984696713102771

Metrics

1 Record Views