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Record W4220795314 · doi:10.1101/2022.03.11.22272276

Risk factors for SARS-CoV-2 infection after primary vaccination with ChAdOx1 nCoV-19 or BNT1262b2 and after booster vaccination with BNT1262b2 or mRNA-1273: a population-based cohort study (COVIDENCE UK)

2022· preprint· en· W4220795314 on OpenAlexfundno aff
Giulia Vivaldi, David A. Jolliffe, Hayley Holt, Florence Tydeman, Mohammad Talaei, Gwyneth A. Davies, Ronan A Lyons, Chris Griffiths, Frank Kee, Aziz Sheikh, Seif O. Shaheen, Adrian R. Martineau

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsnot available
FundersAsthma and Lung UKBritish Heart FoundationNational Institute for Health and Care ResearchCancer Research UKDSM Nutritional ProductsBritish Lung FoundationBarts CharityDiabetes UKUK Research and InnovationRosetrees TrustArthritis SocietyVasculitis UK
KeywordsMedicineVaccinationBooster (rocketry)CohortBooster dosePopulationCohort studyProspective cohort studyImmunologyInternal medicineEnvironmental healthImmunizationImmune system

Abstract

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Abstract Background Little is known about the relative influence of demographic, behavioural, and vaccine-related factors on risk of post-vaccination SARS-CoV-2 infection. We aimed to identify risk factors for SARS-CoV-2 infection after primary and booster vaccinations. Methods We undertook a prospective population-based study in UK adults (≥16 years) vaccinated against SARS-CoV-2, including data from Jan 12, 2021, to Feb 21, 2022. We modelled risk of post-vaccination SARS-CoV-2 infection separately for participants who had completed a primary course of vaccination (two-dose or, in the immunosuppressed, three-dose course of either ChAdOx1 nCoV-19 [ChAdOx1] or BNT1262b2) and for those who had additionally received a booster dose (BNT1262b2 or mRNA-1273). Cox regression models were used to explore associations between sociodemographic, behavioural, clinical, pharmacological, and nutritional factors and breakthrough infection, defined as a self-reported positive result on a lateral flow or reverse transcription PCR (RT-PCR) test for SARS-CoV-2. Models were further adjusted for weekly SARS-CoV-2 incidence at the local (lower tier local authority) level. Findings 14,713 participants were included in the post-primary analysis and 10,665 in the post-booster analysis, with a median follow-up of 203 days (IQR 195–216) in the post-primary cohort and 85 days (66–103) in the post-booster cohort. 1051 (7.1%) participants in the post-primary cohort and 1009 (9.4%) participants in the post-booster cohort reported a breakthrough SARS-CoV-2 infection. A primary course of ChAdOx1 ( vs BNT182b2) was associated with higher risk of infection, both in the post-primary cohort (adjusted hazard ratio 1.63, 95% CI 1.41–1.88) and in the post-booster cohort after boosting with mRNA-1273 (1.29 [1.03–1.61] vs BNT162b2 primary plus BNT162b2 booster). A lower risk of breakthrough infection was associated with older age (post-primary: 0.96 [0.96–0.97] per year; post-booster: 0.97 [0.96–0.98]), whereas a higher risk of breakthrough infection was associated with lower levels of education (post-primary: 1.66 [1.35–2.06] for primary or secondary vs postgraduate; post-booster: 1.36 [1.08–1.71]) and at least three weekly visits to indoor public places (post-primary: 1.38 [1.15–1.66] vs none; post-booster: 1.33 [1.10–1.60]). Conclusions Vaccine type, socioeconomic status, age, and behaviours affect risk of breakthrough SARS-CoV-2 infection following a primary schedule and a booster dose. Research in context Evidence before this study We searched PubMed, medRxiv, and Google Scholar for papers published up to Feb 18, 2022, using the search terms (breakthrough OR post-vaccin*) AND (SARS-CoV-2 OR COVID) AND (disease OR infection) AND (determinant OR “risk factor” OR associat*), with no language restrictions. Existing studies on risk factors for breakthrough SARS-CoV-2 infection among vaccinated individuals have found associations with age, comorbidities, vaccine type, and previous infection; however, findings have been inconsistent across studies. Most studies have been limited to specific subgroups or have focused on severe outcomes, and very few have considered breakthrough infections after a booster dose or have adjusted for behaviours affecting exposure to other people. Added value of this study This study is among the first to provide a detailed analysis of a wide range of risk factors for breakthrough SARS-CoV-2 infection, both after the primary course of vaccination and after a booster dose. Our large study size and detailed data have allowed us to investigate associations with various sociodemographic, clinical, pharmacological, and nutritional factors. Monthly follow-up data have additionally given us the opportunity to consider the effects of behaviours that may have changed across the pandemic, while adjusting for local SARS-CoV-2 incidence. Implications of all the available evidence Our findings add to growing evidence that risk factors for SARS-CoV-2 infection after primary or booster vaccinations can differ to those in unvaccinated populations, with effects attenuated for previously observed risk factors such as body-mass index and Asian ethnicity. The clear difference we observed between the efficacies of ChAdOx1 and BNT162b2 as the primary course of vaccination appears to have been reduced by the use of BNT162b2 boosters, but not by mNRA-1273 boosters. As more countries introduce booster vaccinations, future population-based studies with longer follow-up will be needed to investigate our findings further.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.350
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2022
Admission routes1
Has abstractyes

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