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Retrospectively modeling the effects of increased global vaccine sharing on the COVID-19 pandemic
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Moore, Sam, Hill, Edward M., Dyson, Louise, Tildesley, Michael J. and Keeling, Matt J. (2022) Retrospectively modeling the effects of increased global vaccine sharing on the COVID-19 pandemic. Nature Medicine . doi:10.1038/s41591-022-02064-y ISSN 1078-8956. (In Press)
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Official URL: http://dx.doi.org/10.1038/s41591-022-02064-y
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has caused considerable morbidity and mortality worldwide. The protection provided by vaccines and booster doses offered a method of mitigating severe clinical outcomes and mortality. However, by the end of 2021, the global distribution of vaccines was highly heterogeneous, with some countries gaining over 90% coverage in adults, whereas others reached less than 2%. In this study, we used an age-structured model of SARS-CoV-2 dynamics, matched to national data from 152 countries in 2021, to investigate the global impact of different potential vaccine sharing protocols that attempted to address this inequity. We quantified the effects of implemented vaccine rollout strategies on the spread of SARS-CoV-2, the subsequent global burden of disease and the emergence of novel variants. We found that greater vaccine sharing would have lowered the total global burden of disease, and any associated increases in infections in previously vaccine-rich countries could have been mitigated by reduced relaxation of non-pharmaceutical interventions. Our results reinforce the health message, pertinent to future pandemics, that vaccine distribution proportional to wealth, rather than to need, may be detrimental to all.
| 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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| Library of Congress Subject Headings (LCSH): | COVID-19 Pandemic, 2020- , COVID-19 vaccines , COVID-19 (Disease) -- Prevention -- Mathematical models, COVID-19 vaccines -- Mathematical models | ||||||||||||||||||
| Journal or Publication Title: | Nature Medicine | ||||||||||||||||||
| Publisher: | Nature Publishing Group | ||||||||||||||||||
| ISSN: | 1078-8956 | ||||||||||||||||||
| Official Date: | 27 October 2022 | ||||||||||||||||||
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| DOI: | 10.1038/s41591-022-02064-y | ||||||||||||||||||
| Status: | Peer Reviewed | ||||||||||||||||||
| Publication Status: | In Press | ||||||||||||||||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||||||||
| Date of first compliant deposit: | 3 November 2022 | ||||||||||||||||||
| Date of first compliant Open Access: | 4 November 2022 | ||||||||||||||||||
| RIOXX Funder/Project Grant: |
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