Naz, Rehana and Zavrakli, Eleni and Parnell, Andrew and Malone, David and Duffy, Ken and Dey, Subhrakanti (2023) Optimal age-specific vaccination control for COVID-19: An Irish case study. PLOS ONE, 18 (9). e0290974. ISSN 1932-6203

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Abstract

The outbreak of a novel coronavirus causing severe acute respiratory syndrome in December 2019 has escalated into a worldwide pandemic. In this work, we propose a compartmental model to describe the dynamics of transmission of infection and use it to obtain the optimal vaccination control. The model accounts for the various stages of the vaccination, and the optimisation is focused on minimising the infections to protect the population and relieve the healthcare system. As a case study, we selected the Republic of Ireland. We use data provided by Ireland’s COVID-19 Data-Hub and simulate the evolution of the pandemic with and without the vaccination in place for two different scenarios, one representative of a national lockdown situation and the other indicating looser restrictions in place. One of the main findings of our work is that the optimal approach would involve a vaccination programme where the older population is vaccinated in larger numbers earlier while simultaneously part of the younger population also gets vaccinated to lower the risk of transmission between groups. We compare our simulated results with those of the vaccination policy taken by the Irish government to explore the advantages of our optimisation method. Our comparison suggests that a similar reduction in cases may have been possible even with a reduced set of vaccinations available for use.

Item Type:	Article
Keywords:	Age groups; Analysis; Biology and Life Sciences; Case reports; Case studies; China; Control theory; Coronaviruses; COVID-19; COVID-19 vaccines;
Academic Unit:	Faculty of Science and Engineering > Mathematics and Statistics Faculty of Science and Engineering > Research Institutes > Hamilton Institute Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
Item ID:	18800
Identification Number:	https://doi.org/10.1371/journal.pone.0290974
Depositing User:	Andrew Parnell
Date Deposited:	22 Aug 2024 13:17
Journal or Publication Title:	PLOS ONE
Publisher:	Public Library of Science
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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