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)
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».