Optimality of maximal-effort vaccination
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Published version
Author(s)
Penn, Matthew J
Donnelly, Christl A
Type
Journal Article
Abstract
It is widely acknowledged that vaccinating at maximal effort in the face of an ongoing epidemic is the best strategy to minimise infections and deaths from the disease. Despite this, no one has proved that this is guaranteed to be true if the disease follows multi-group SIR (Susceptible-Infected-Recovered) dynamics. This paper provides a novel proof of this principle for the existing SIR framework, showing that the total number of deaths or infections from an epidemic is decreasing in vaccination effort. Furthermore, it presents a novel model for vaccination which assumes that vaccines assigned to a subgroup are distributed randomly to the unvaccinated population of that subgroup. It suggests, using COVID-19 data, that this more accurately captures vaccination dynamics than the model commonly found in the literature. However, as the novel model provides a strictly larger set of possible vaccination policies, the results presented in this paper hold for both models.
Date Issued
2023-08
Date Acceptance
2023-06-02
Citation
Bulletin of Mathematical Biology, 2023, 85 (8), pp.1-71
ISSN
0092-8240
Publisher
Springer
Start Page
1
End Page
71
Journal / Book Title
Bulletin of Mathematical Biology
Volume
85
Issue
8
Copyright Statement
© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/37351716
Subjects
COVID-19
Epidemics
Humans
Mathematical Concepts
Models, Biological
Vaccination
Epidemics
Epidemiology
SIR Modelling
Vaccination
Publication Status
Published
Coverage Spatial
United States
Article Number
73
Date Publish Online
2023-06-23