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Vaccine escape in a heterogeneous population : insights for SARS-CoV-2 from a simple model
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Gog, Julia R., Hill, Edward M., Danon, Leon and Thompson, Robin N. (2021) Vaccine escape in a heterogeneous population : insights for SARS-CoV-2 from a simple model. Royal Society Open Science, 8 (7). 210530. doi:10.1098/rsos.210530 ISSN 2054-5703.
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WRAP-Vaccine-escape-heterogeneous-populations-SARS-CoV-2-simple-model-2021.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (5Mb) | Preview |
Official URL: https://doi.org/10.1098/rsos.210530
Abstract
As a countermeasure to the SARS-CoV-2 pandemic, there has been swift development and clinical trial assessment of candidate vaccines, with subsequent deployment as part of mass vaccination campaigns. However, the SARS-CoV-2 virus has demonstrated the ability to mutate and develop variants, which can modify epidemiological properties and potentially also the effectiveness of vaccines. The widespread deployment of highly effective vaccines may rapidly exert selection pressure on the SARS-CoV-2 virus directed towards mutations that escape the vaccine-induced immune response. This is particularly concerning while infection is widespread. By developing and analysing a mathematical model of two population groupings with differing vulnerability and contact rates, we explore the impact of the deployment of vaccines among the population on the reproduction ratio, cases, disease abundance and vaccine escape pressure. The results from this model illustrate two insights: (i) vaccination aimed at reducing prevalence could be more effective at reducing disease than directly vaccinating the vulnerable; (ii) the highest risk for vaccine escape can occur at intermediate levels of vaccination. This work demonstrates a key principle: the careful targeting of vaccines towards particular population groups could reduce disease as much as possible while limiting the risk of vaccine escape.
Item Type: | Journal Article | ||||||
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Subjects: | Q Science > QR Microbiology R Medicine > RA Public aspects of medicine |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) Faculty of Science, Engineering and Medicine > Science > Mathematics |
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SWORD Depositor: | Library Publications Router | ||||||
Library of Congress Subject Headings (LCSH): | COVID-19 (Disease) , COVID-19 (Disease) -- Epidemiology -- Mathematical models , COVID-19 (Disease) -- Forecasting -- Mathematical models , COVID-19 (Disease) -- Vaccination -- Mathematical models , Coronavirus infections, Vaccines | ||||||
Journal or Publication Title: | Royal Society Open Science | ||||||
Publisher: | The Royal Society | ||||||
ISSN: | 2054-5703 | ||||||
Official Date: | 14 July 2021 | ||||||
Dates: |
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Volume: | 8 | ||||||
Number: | 7 | ||||||
Article Number: | 210530 | ||||||
DOI: | 10.1098/rsos.210530 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||
Date of first compliant deposit: | 14 July 2021 | ||||||
Date of first compliant Open Access: | 15 July 2021 | ||||||
RIOXX Funder/Project Grant: |
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