Imperial College London
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Professor Christl Donnelly CBE FMedSci FRS

Faculty of Medicine, School of Public Health

Visiting Professor
 
 
 
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Contact

 

c.donnelly Website

 
 
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Location

 

School of Public HealthWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@article{Penn:2022:10.1101/2022.06.02.22275908,
author = {Penn, MJ and Donnelly, CA},
doi = {10.1101/2022.06.02.22275908},
title = {Asymptotic analysis of optimal vaccination policies},
url = {http://dx.doi.org/10.1101/2022.06.02.22275908},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - <jats:title>Abstract</jats:title><jats:p>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 SIR (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.</jats:p><jats:sec><jats:title>Author summary</jats:title><jats:p>The COVID-19 pandemic has illustrated the importance of vaccination programs in preventing infections and deaths from an epidemic. A common feature of vaccination programs across the world has been a prioritisation of different groups within each country’s population, particularly those who are more vulnerable to the disease. Finding the best priority order is crucial, but may be complicated and difficult to justify to policy-makers and the public. In this paper, we consider two extreme cases where the best prioritisation order can be mathematically derived. Firstly, we consider the case of a population with a very
AU  - Penn,MJ
AU  - Donnelly,CA
DO  - 10.1101/2022.06.02.22275908
PY  - 2022///
TI  - Asymptotic analysis of optimal vaccination policies
UR  - http://dx.doi.org/10.1101/2022.06.02.22275908
ER  -
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