Seroprevalence of rubella antibodies and determinants of susceptibility to rubella in a cohort of pregnant women in Canada, 2008–2011
Bibliographic record
Abstract
Long term control of rubella and congenital rubella syndrome relies on high population-level immunity against rubella, particularly among women of childbearing age. In Canada, all pregnant women should be screened so that susceptible new mothers can be offered vaccination for rubella before discharge. This study was undertaken to estimate rubella susceptibility in a cohort of pregnant women in Canada and to identify associated socio-economic and demographic factors. Biobanked plasma samples were obtained from the Maternal-Infant Research on Environmental Chemicals (MIREC) study, in which pregnant women were recruited between 2008 and 2011. Socio-demographic characteristics and obstetric histories were collected. Second trimester plasma samples (n=1,752) were tested for rubella-specific IgG using an in-house enzyme-linked immunosorbent assay. The percentage of women with IgG titers <5IU/mL, 5-10IU/mL, and ≥10IU/mL were 2.3%, 10.1%, and 87.6%, respectively. Rates of seronegativity, defined as <5IU/mL, were 3.1% in women who had no previous live birth and 1.6% in women who had given birth previously. Among the latter group, seronegativity was higher in women with high school education or less (adjusted OR (aOR) 5.93, 95% CI 2.08-16.96) or with a college or trade school diploma (aOR 3.82, 95% CI 1.45-10.12), compared to university graduates, and those born outside Canada (aOR 2.60, 95% CI 1.07-6.31). In conclusion, a large majority of pregnant women were found to be immune to rubella. Further research is needed to understand inequalities in vaccine uptake or access, and more effort is needed to promote catch-up measles-mumps-rubella vaccination among socioeconomically disadvantaged and immigrant women of childbearing age.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".