The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Vaccination and non-pharmaceutical interventions for COVID-19: a mathematical modelling study
Open accessAbstract
BACKGROUND: The dynamics of vaccination against SARS-CoV-2 are complicated by age-dependent factors, changing levels of infection, and the relaxation of non-pharmaceutical interventions (NPIs) as the perceived risk declines, necessitating the use of mathematical models. Our aims were to use epidemiological data from the UK together with estimates of vaccine efficacy to predict the possible long-term dynamics of SARS-CoV-2 under the planned vaccine rollout. METHODS: In this study, we used a mathematical model structured by age and UK region, fitted to a range of epidemiological data in the UK, which incorporated the planned rollout of a two-dose vaccination programme (doses 12 weeks apart, protection onset 14 days after vaccination). We assumed default vaccine uptake of 95% in those aged 80 years and older, 85% in those aged 50-79 years, and 75% in those aged 18-49 years, and then varied uptake optimistically and pessimistically. Vaccine efficacy against symptomatic disease was assumed to be 88% on the basis of Pfizer-BioNTech and Oxford-AstraZeneca vaccines being administered in the UK, and protection against infection was varied from 0% to 85%. We considered the combined interaction of the UK vaccination programme with multiple potential future relaxations (or removals) of NPIs, to predict the reproduction number (R) and pattern of daily deaths and hospital admissions due to COVID-19 from January, 2021, to January, 2024. FINDINGS: We estimate that vaccination alone is insufficient to contain the outbreak. In the absence of NPIs, even with our most optimistic assumption that the vaccine will prevent 85% of infections, we estimate R to be 1·58 (95% credible intervals [CI] 1·36-1·84) once all eligible adults have been offered both doses of the vaccine. Under the default uptake scenario, removal of all NPIs once the vaccination programme is complete is predicted to lead to 21 400 deaths (95% CI 1400-55 100) due to COVID-19 for a vaccine that prevents 85% of infections, although this number increases to 96 700 deaths (51 800-173 200) if the vaccine only prevents 60% of infections. Although vaccination substantially reduces total deaths, it only provides partial protection for the individual; we estimate that, for the default uptake scenario and 60% protection against infection, 48·3% (95% CI 48·1-48·5) and 16·0% (15·7-16·3) of deaths will be in individuals who have received one or two doses of the vaccine, respectively. INTERPRETATION: For all vaccination scenarios we investigated, our predictions highlight the risks associated with early or rapid relaxation of NPIs. Although novel vaccines against SARS-CoV-2 offer a potential exit strategy for the pandemic, success is highly contingent on the precise vaccine properties and population uptake, both of which need to be carefully monitored. FUNDING: National Institute for Health Research, Medical Research Council, and UK Research and Innovation.
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Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine
Polack, F. P., Thomas, S. J., Kitchin, N., Absalon, J., Gurtman, A., Lockhart, S., Perez, J. L., Pérez Marc, G., Moreira, E. D., Zerbini, C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2034577 · Cited by 14,592
Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine
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Self-citationModel-informed COVID-19 vaccine prioritization strategies by age and serostatus
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Cited by
Bouton, T. C., Lodi, S., Turcinovic, J., Schaeffer, B., Weber, S. E., Quinn, E., Korn, C., Steiner, J., Schechter-Perkins, E. M., Duffy, E., et al. (2021) · Open Forum Infectious Diseases · doi:10.1093/ofid/ofab465 · Cited by 49
Swart, L.-A., Taliep, N., Ismail, G., & van Niekerk, A. (2022) · BMC Public Health · doi:10.1186/s12889-022-13845-y · Cited by 14
Overcoming COVID-19 in China despite shortcomings of the public health system: what can we learn?
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Metadata
- Authors
- Moore, S., Hill, E. M., Tildesley, M. J., Dyson, L., & Keeling, M. J.
- Venue
- The Lancet Infectious Diseases
- Publisher
- Elsevier BV
- Published
- 2021-06
- Volume
- 21
- Issue
- 6
- Pages
- 793-802
- ISSN
- 1473-3099 (ISSN-L)
- OpenAlex
- W3136624297
- Cited by
- 537
- References
- 24
- FWCI
- 46.86
- Type
- journal article
- Language
- en
- Open access
- hybrid
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