Immune responses to Sinopharm/ <scp>BBIBP‐CorV</scp> in individuals in Sri Lanka
Bibliographic record
Abstract
As there are limited data of the immunogenicity of the Sinopharm/BBIBP-CorV in different populations, antibody responses against different SARS-CoV-2 variants of concern and T cell responses, we investigated the immunogenicity of the vaccine, in individuals in Sri Lanka. SARS-CoV-2-specific antibodies were measured in 282 individuals who were seronegative at baseline, and ACE2 receptor blocking antibodies, antibodies to the receptor-binding domain (RBD) of the wild-type (WT), alpha, beta and delta variants, ex vivo and cultured IFNγ ELISpot assays, intracellular cytokine secretion assays and B cell ELISpot assays were carried out in a sub cohort of the vaccinees at 4 and 6 weeks (2 weeks after the second dose). Ninety-five percent of the vaccinees seroconverted, although the seroconversion rates were significantly lower (p < 0.001) in individuals >60 years (93.3%) compared to those who were 20-39 years (98.9%); 81.25% had ACE2 receptor blocking antibodies at 6 weeks, and there was no difference in these antibody titres in vaccine sera compared to convalescent sera (p = 0.44). Vaccinees had significantly less (p < 0.0001) antibodies to the RBD of WT and alpha, although there was no difference in antibodies to the RBD of beta and delta compared to convalescent sera; 27.7% of 46.4% of vaccinees had ex vivo IFNγ and cultured ELISpot responses respectively, and IFNγ and CD107a responses were detected by flow cytometry. Sinopharm/BBIBP-CorV appeared to induce a similar level of antibody responses against ACE2 receptor, delta and beta as seen following natural infection.
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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) | 0.001 | 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".