Evidence map›Paper›PMID 34716320›Full record

ArticleNature communications2021

Anti-spike antibody response to natural SARS-CoV-2 infection in the general population.

Jia Wei, Philippa C Matthews, Nicole Stoesser, Thomas Maddox, Luke Lorenzi, Ruth Studley, John I Bell, John N Newton, Jeremy Farrar, Ian Diamond and 12 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
77citing papers in PubMed, 1 pooled it
8.6field-weighted citation impact, top 2% 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

77 citing papers in PubMed, 1 synthesis or guideline pooled it, 147 citations in OpenAlex.

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17 more citing papers are in PubMed but not listed here.

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

22 authors at 15 institutions in 1 country.

Jia WeiNuffield Department of Medicine, University of Oxford, Oxford, UK.
Philippa C MatthewsNuffield Department of Medicine, University of Oxford, Oxford, UK.
Nicole StoesserNuffield Department of Medicine, University of Oxford, Oxford, UK.ORCID 0000-0002-4508-7969
Thomas MaddoxOffice for National Statistics, Newport, UK.
Luke LorenziOffice for National Statistics, Newport, UK.
Ruth StudleyOffice for National Statistics, Newport, UK.
John I BellOffice of the Regius Professor of Medicine, University of Oxford, Oxford, UK.
John N NewtonHealth Improvement Directorate, Public Health England, London, UK.
Jeremy FarrarWellcome Trust, London, UK.
Ian DiamondOffice for National Statistics, Newport, UK.
Emma RourkeOffice for National Statistics, Newport, UK.
Alison HowarthNuffield Department of Medicine, University of Oxford, Oxford, UK.
Brian D MarsdenNuffield Department of Medicine, University of Oxford, Oxford, UK.
Sarah HoosdallyNuffield Department of Medicine, University of Oxford, Oxford, UK.
E Yvonne JonesNuffield Department of Medicine, University of Oxford, Oxford, UK.
David I StuartNuffield Department of Medicine, University of Oxford, Oxford, UK.
Derrick W CrookNuffield Department of Medicine, University of Oxford, Oxford, UK.
Tim E A PetoNuffield Department of Medicine, University of Oxford, Oxford, UK.
Koen B Pouwels *Nuffield Department of Medicine, University of Oxford, Oxford, UK.ORCID 0000-0001-7097-8950
A Sarah Walker *Nuffield Department of Medicine, University of Oxford, Oxford, UK.
David W Eyre *Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, UK. david.eyre@bdi.ox.ac.uk.ORCID 0000-0001-5095-6367
COVID-19 Infection Survey team
University of Oxford · GBOffice for National Statistics · GBIQVIA (United Kingdom) · GBJohn Radcliffe Hospital · GBScottish Government · GBOpen Data Institute · GBPublic Health Scotland · GBDepartment of Health and Social Care · GBOxford University Hospitals NHS Trust · GBPublic Health England · GBUniversity of Manchester · GBWelsh Government · GBNational Institute for Health Research · GBNuffield Orthopaedic Centre · GBWellcome Trust · GB

Funding

Medical Research Council MC_UU_00008/6Medical Research Council MC_UU_12023/22Medical Research Council MR/V001329/1Wellcome Trust
6 · The paper itself

Abstract

Understanding the trajectory, duration, and determinants of antibody responses after SARS-CoV-2 infection can inform subsequent protection and risk of reinfection, however large-scale representative studies are limited. Here we estimated antibody response after SARS-CoV-2 infection in the general population using representative data from 7,256 United Kingdom COVID-19 infection survey participants who had positive swab SARS-CoV-2 PCR tests from 26-April-2020 to 14-June-2021. A latent class model classified 24% of participants as 'non-responders' not developing anti-spike antibodies, who were older, had higher SARS-CoV-2 cycle threshold values during infection (i.e. lower viral burden), and less frequently reported any symptoms. Among those who seroconverted, using Bayesian linear mixed models, the estimated anti-spike IgG peak level was 7.3-fold higher than the level previously associated with 50% protection against reinfection, with higher peak levels in older participants and those of non-white ethnicity. The estimated anti-spike IgG half-life was 184 days, being longer in females and those of white ethnicity. We estimated antibody levels associated with protection against reinfection likely last 1.5-2 years on average, with levels associated with protection from severe infection present for several years. These estimates could inform planning for vaccination booster strategies.

Indexed as

AdultAgedAntibodies, ViralAntibody FormationBayes TheoremCOVID-19FemaleHumansImmunoglobulin GMaleMiddle AgedSARS-CoV-2Antibodies, ViralImmunoglobulin G

Identifiers

PMID34716320
PMCPMC8556331
OpenAlexW3178962125

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.