Publications

BibTex format

@article{Penn:2023:10.1007/s11538-023-01179-8,
author = {Penn, MJ and Donnelly, CA},
doi = {10.1007/s11538-023-01179-8},
journal = {Bulletin of Mathematical Biology},
pages = {1--71},
title = {Optimality of maximal-effort vaccination},
url = {http://dx.doi.org/10.1007/s11538-023-01179-8},
volume = {85},
year = {2023}
}

Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Penn,MJ
AU  - Donnelly,CA
DO  - 10.1007/s11538-023-01179-8
EP  - 71
PY  - 2023///
SN  - 0092-8240
SP  - 1
TI  - Optimality of maximal-effort vaccination
T2  - Bulletin of Mathematical Biology
UR  - http://dx.doi.org/10.1007/s11538-023-01179-8
UR  - https://www.ncbi.nlm.nih.gov/pubmed/37351716
UR  - https://link.springer.com/article/10.1007/s11538-023-01179-8
UR  - http://hdl.handle.net/10044/1/105213
VL  - 85
ER  -

Download

Professor Christl Donnelly CBE FMedSci FRS

Contact

Location

Summary

Citation

BibTex format

RIS format (EndNote, RefMan)