Evidence map›Paper›PMID 35307024›Full record

ArticleBMC infectious diseases2022

Effectiveness of the BNT162b2 (Pfizer-BioNTech) and the ChAdOx1 nCoV-19 (Oxford-AstraZeneca) vaccines for reducing susceptibility to infection with the Delta variant (B.1.617.2) of SARS-CoV-2.

Karan Pattni, Daniel Hungerford, Sarah Adams, Iain Buchan, Christopher P Cheyne, Marta García-Fiñana, Ian Hall, David M Hughes, Christopher E Overton, Xingna Zhang and 1 more

Abstract read
In one paragraph

Article in BMC infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
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

11 authors.

Karan PattniDepartment of Mathematical Sciences, University of Liverpool, Liverpool, UK.
Daniel HungerfordCentre for Global Vaccine Research, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK.
Sarah AdamsGraphnet Health, Milton Keynes, UK.
Iain BuchanInstitute of Population Health, University of Liverpool, Liverpool, UK.
Christopher P CheyneDepartment of Health Data Science, University of Liverpool, Liverpool, UK.
Marta García-FiñanaDepartment of Health Data Science, University of Liverpool, Liverpool, UK.
Ian HallDepartment of Mathematics and School of Health Sciences, University of Manchester, Manchester, UK.
David M HughesDepartment of Health Data Science, University of Liverpool, Liverpool, UK.
Christopher E OvertonDepartment of Mathematics and School of Health Sciences, University of Manchester, Manchester, UK.
Xingna ZhangInstitute of Population Health, University of Liverpool, Liverpool, UK.
Kieran J SharkeyDepartment of Mathematical Sciences, University of Liverpool, Liverpool, UK. kjs@liverpool.ac.uk.ORCID http://orcid.org/0000-0002-7210-9246

Funding

Engineering and Physical Sciences Research Council EP/T031727/1National Institute for Health Research NIHR200910National Institute for Health Research (GB) PDF-2018-11-ST2-006
6 · The paper itself

Abstract

backgroundFrom January to May 2021 the alpha variant (B.1.1.7) of SARS-CoV-2 was the most commonly detected variant in the UK. Following this, the Delta variant (B.1.617.2) then became the predominant variant. The UK COVID-19 vaccination programme started on 8th December 2020. Prior to the Delta variant, most vaccine effectiveness studies focused on the alpha variant. We therefore aimed to estimate the effectiveness of the BNT162b2 (Pfizer-BioNTech) and the ChAdOx1 nCoV-19 (Oxford-AstraZeneca) vaccines in preventing symptomatic and asymptomatic infection with respect to the Delta variant in a UK setting.

methodsWe used anonymised public health record data linked to infection data (PCR) using the Combined Intelligence for Population Health Action resource. We then constructed an SIR epidemic model to explain SARS-CoV-2 infection data across the Cheshire and Merseyside region of the UK. Vaccines were assumed to be effective after 21 days for 1 dose and 14 days for 2 doses.

resultsWe determined that the effectiveness of the Oxford-AstraZeneca vaccine in reducing susceptibility to infection is 39% (95% credible interval [34, 43]) and 64% (95% credible interval [61, 67]) for a single dose and a double dose respectively. For the Pfizer-BioNTech vaccine, the effectiveness is 20% (95% credible interval [10, 28]) and 84% (95% credible interval [82, 86]) for a single-dose and a double dose respectively.

conclusionVaccine effectiveness for reducing susceptibility to SARS-CoV-2 infection shows noticeable improvement after receiving two doses of either vaccine. Findings also suggest that a full course of the Pfizer-BioNTech provides the optimal protection against infection with the Delta variant. This reinforces the need to complete the full course programme to maximise individual protection and reduce transmission.

Indexed as

COVID-19Viral VaccinesBNT162 VaccineChAdOx1 nCoV-19COVID-19 VaccinesHumansSARS-CoV-2BNT162 VaccineChAdOx1 nCoV-19COVID-19 VaccinesViral VaccinesCOVID-19EffectivenessInfectious diseaseModellingSARS-CoV-2SIRVaccine

Identifiers

PMID35307024
PMCPMC8934524

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Registered trials

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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.