Evidence map›Paper›PMID 38016000›Full record

ArticlePLoS medicine2023

Long-term vaccination strategies to mitigate the impact of SARS-CoV-2 transmission: A modelling study.

Alexandra B Hogan, Sean L Wu, Jaspreet Toor, Daniela Olivera Mesa, Patrick Doohan, Oliver J Watson, Peter Winskill, Giovanni Charles, Gregory Barnsley, Eleanor M Riley and 3 more

Open access · goldAbstract read
In one paragraph

Article in PLoS medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.5field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 19 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 5 institutions in 3 countries.

Alexandra B HoganSchool of Population Health, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia.ORCID 0000-0002-6271-9921
Sean L WuInstitute for Health Metrics and Evaluation, University of Washington, Seattle, United States of America.ORCID 0000-0002-5781-9493
Jaspreet ToorMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.
Daniela Olivera MesaMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-6190-2855
Patrick DoohanMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.
Oliver J WatsonMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0003-2374-0741
Peter WinskillMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0003-3001-4959
Giovanni CharlesMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-7024-1200
Gregory BarnsleyMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0001-7972-0737
Eleanor M RileyInstitute of Immunology and Infection Research, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom.
David S KhouryKirby Institute, University of New South Wales, Sydney, Australia.ORCID 0000-0002-2663-1551
Neil M FergusonMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-1154-8093
Azra C GhaniMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-0007-4910
Imperial College London · GBUNSW Sydney · AULondon School of Hygiene & Tropical Medicine · GBUniversity of Edinburgh · GBUniversity of Washington · US

Funding

Wellcome Trust
6 · The paper itself

Abstract

backgroundVaccines have reduced severe disease and death from Coronavirus Disease 2019 (COVID-19). However, with evidence of waning efficacy coupled with continued evolution of the virus, health programmes need to evaluate the requirement for regular booster doses, considering their impact and cost-effectiveness in the face of ongoing transmission and substantial infection-induced immunity. METHODS AND

findingsWe developed a combined immunological-transmission model parameterised with data on transmissibility, severity, and vaccine effectiveness. We simulated Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transmission and vaccine rollout in characteristic global settings with different population age-structures, contact patterns, health system capacities, prior transmission, and vaccine uptake. We quantified the impact of future vaccine booster dose strategies with both ancestral and variant-adapted vaccine products, while considering the potential future emergence of new variants with modified transmission, immune escape, and severity properties. We found that regular boosting of the oldest age group (75+) is an efficient strategy, although large numbers of hospitalisations and deaths could be averted by extending vaccination to younger age groups. In countries with low vaccine coverage and high infection-derived immunity, boosting older at-risk groups was more effective than continuing primary vaccination into younger ages in our model. Our study is limited by uncertainty in key parameters, including the long-term durability of vaccine and infection-induced immunity as well as uncertainty in the future evolution of the virus.

conclusionsOur modelling suggests that regular boosting of the high-risk population remains an important tool to reduce morbidity and mortality from current and future SARS-CoV-2 variants. Our results suggest that focusing vaccination in the highest-risk cohorts will be the most efficient (and hence cost-effective) strategy to reduce morbidity and mortality.

Indexed as

COVID-19VaccinesHumansSARS-CoV-2VaccinationVaccines

Identifiers

PMID38016000
PMCPMC10715640
OpenAlexW4389076444

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.