BBIBP-CorV (Sinopharm) vaccination- induced immunity is affected by age, gender and prior COVID-19 and activates responses to spike and other antigens
Bibliographic record
Abstract
Abstract Long-term solutions against SARS-CoV-2 infections require understanding of immune protection induced by different vaccine COVID-19 formulations. We investigated humoral and cellular immunity induced by Sinopharm (BBIBP-CorV) in a region of high SARS-CoV-2 seroprevalence. Levels of IgG antibodies to SARS-CoV-2 spike protein and its receptor-binding domain (RBD) were determined 24-weeks. Cellular immunity was investigated using a commercially available IFN-γ release assay to SARS-CoV-2 spike (Ag1 and 2) and extended genome antigens (Ag3). Increasing IgG seropositivity to Spike protein and RBD was observed post-vaccination. Seropositivity was reduced in those over 50 years and raised in females and those with prior COVID-19. After 20 weeks post-vaccination, only one third of participants had positive T cell responses to SARS-CoV-2 antigens. Prior COVID-19 impacted IFNγ responses, with reactivity enhanced in those infected earlier. The frequency of IFNγ responses was highest to extended genome antigen set. Overall, BBIBP-CorV- induced antibody responses were impacted by age, gender and prior COVID-19. Cellular immunity was present in a limited number of individuals after 20 weeks but was enhanced by prior infection. This suggests the need for booster vaccinations in older individuals. BBIBP-CorV-induced cellular activation is broader than to spike, requiring further study to understand how to monitor vaccine effectiveness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".