Asymptotic analysis of optimal vaccination policies
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Published version
Author(s)
Penn, Matthew J
Donnelly, Christl A
Type
Journal Article
Abstract
Targeted vaccination policies can have a significant impact on the number of infections and deaths in an epidemic. However, optimising such policies is complicated, and the resultant solution may be difficult to explain to policy-makers and to the public. The key novelty of this paper is a derivation of the leading-order optimal vaccination policy under multi-group susceptible–infected–recovered dynamics in two different cases. Firstly, it considers the case of a small vulnerable subgroup in a population and shows that (in the asymptotic limit) it is optimal to vaccinate this group first, regardless of the properties of the other groups. Then, it considers the case of a small vaccine supply and transforms the optimal vaccination problem into a simple knapsack problem by linearising the final size equations. Both of these cases are then explored further through numerical examples, which show that these solutions are also directly useful for realistic parameter values. Moreover, the findings of this paper give some general principles for optimal vaccination policies which will help policy-makers and the public to understand the reasoning behind optimal vaccination programs in more generic cases.
Date Issued
2023-03
Date Acceptance
2022-12-24
Citation
Bulletin of Mathematical Biology, 2023, 85 (3), pp.1-72
ISSN
0092-8240
Publisher
Springer
Start Page
1
End Page
72
Journal / Book Title
Bulletin of Mathematical Biology
Volume
85
Issue
3
Copyright Statement
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
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Subjects
Science & Technology
Life Sciences & Biomedicine
Biology
Mathematical & Computational Biology
Life Sciences & Biomedicine - Other Topics
Vaccination
Epidemiology
Epidemics
SIR modelling
EPIDEMIC MODEL
AGE
INFLUENZA
ALLOCATION
Publication Status
Published
Article Number
15
Date Publish Online
2023-01-20