Additional file 1 of Correlates of protection and determinants of SARS-CoV-2 breakthrough infections 1 year after third dose vaccination
Notice bibliographique
Résumé
Additional file 1. Correlates of protection and determinants of SARS-CoV-2 breakthroughs one year after third dose vaccination. Supplementary Figure 1. Comparison of antibody levels against S from Delta and Wuhan variants following hybrid immunity or vaccination alone. Supplementary Figure 2. Evolution and comparison of IgM levels following hybrid immunity or vaccination alone. Supplementary Figure 3. Evolution and comparison of antibody levels after booster vaccination according to the timing of the last SARS-CoV-2 infection in individuals vaccinated with 3 doses. Supplementary Figure 4. Evolution and comparison of IgM levels after booster vaccination according to the timing of the last SARS-CoV-2 infection in individuals vaccinated with 3 doses. Supplementary Figure 5. Comparison of antibody levels against S from Delta and Omicron variants after booster vaccination according to last SARS-CoV-2 infection in individuals vaccinated with 3 doses. Supplementary Figure 6. Linear regression analysis of the association of several factors with M24 IgG antibody levels in infected individuals vaccinated with 3 doses. Supplementary Figure 7. Evolution and comparison of antibody levels after primary vaccination with BNT162b2 or mRNA-1273 followed by booster vaccination with mRNA-1273. Supplementary Figure 8. Comparison of antibody levels against S from Delta and Omicron variants after primary vaccination with BNT162b2 or mRNA-1273 followed by booster vaccination with mRNA-1273. Supplementary Figure 9. Linear regression analysis of the association of several factors with M24 IgG levels in naïve individuals vaccinated with 3 doses. Supplementary Figure 10. Association of IgA levels at M24 with post-M24 breakthrough infections. Supplementary Figure 11. Predicted risk of breakthrough infection as a function of IgG antibody levels measured at M24. Supplementary Figure 12. Correlations between the different IgG, IgA and IgM antibody levels at M24. Supplementary Figure 13. Penalized Cox regression model to identify non-collinear antibodies highly associated with protection against breakthrough infection. Supplementary Figure 14. Heatmap of hierarchical clustering of study participants based on antibody levels at M24. Supplementary Figure 15. Directed acyclic graph (DAG) which reports our causal assumptions for generating the models to assess the total effect of a given factor on antibody levels at M24 (MFI) on naïve and infected individuals with 3 doses. Supplementary Figure 16. Directed acyclic graph (DAG) which reports our causal assumptions for generating the models to assess the total effect of a given factor on antibody levels at M24 (MFI) on naïve individuals with 3 doses. Supplementary Figure 17. Directed acyclic graph (DAG) which reports our causal assumptions for generating the models to assess the total effect of a given factor on antibody levels at M24 (MFI) on infected individuals with 3 doses. Supplementary Figure 18. Directed acyclic graph (DAG) which reports our causal assumptions for generating the models to assess the effect of booster vaccination (third dose) on antibody levels at M24 (MFI). Supplementary Figure 19. Directed acyclic graph (DAG) which reports our causal assumptions for generating the models to assess the total effect of several factors on breakthrough infection post-M24 on individuals vaccinated with 3 doses. Supplementary Figure 20. Directed acyclic graph (DAG) which reports our causal assumptions for generating the models to assess the total effect of several factors on breakthrough infection post-M24 on individuals vaccinated with 2 or 3 doses. Supplementary Table 1. Seropositivity status of study participants at M24. Supplementary Table 2. Summary of linear regression models to assess the association of a third dose of mRNA vaccine with IgG levels as compared to two doses. Supplementary Table 3. Summary of univariable Cox Regression models for the association of antibody levels with breakthrough infection in individuals vaccinated with two or three doses of mRNA vaccine. Supplementary Table 4. Summary of univariable Cox Regression models to assess the association between several clinicodemographic factors with breakthrough infection in individuals vaccinated with two or three doses of mRNA vaccine.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,037 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,830 | 0,107 |
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 source (Gemma direct ou Codex distillé), 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 ».