The half-life of maternal transplacental antibodies against diphtheria, tetanus, and pertussis in infants: an individual participant data meta-analysis
Bibliographic record
Abstract
There are few reliable estimates of the half-lives of maternal antibodies to the antigens found in the primary series vaccines. We aimed to calculate the half-lives of passively acquired diphtheria, tetanus and pertussis (DTP) antibodies in infants. We aimed to determine whether decay rates varied according to country, maternal age, gestational age, birthweight, World Bank income classifications, or vaccine received by the mother during pregnancy. De-identified data from infants born to women taking part in 10 studies, in 9 countries (UK, Belgium, Thailand, Vietnam, Canada, Pakistan, USA, Guatemala and the Netherlands) were combined in an individual participant data meta-analysis. Blood samples were taken at two timepoints before any DTP-containing vaccines were received by the infant: at birth and at 2-months of age. Decay rates for each antigen were log2-transformed and a mixed effects model was applied. Half-lives were calculated by taking the reciprocal of the absolute value of the mean decay rates. Data from 1426 mother-infant pairs were included in the analysis. The half-lives of the 6 antigen-specific maternal antibodies of interest were similar, with point estimates ranging from 28.7 (95% CI: 24.4 – 35) days for tetanus toxoid antibodies to 35.1 (95% CI: 30.7 – 41.1) days for pertactin antibodies. The decay of maternal antibodies did not significantly differ by maternal age, gestational age, birthweight, maternal vaccination status or type of vaccine administered. Maternal antibodies decay at different rates for the different antigens; however, the magnitude of the difference is small. Decay rates are not modified by key demographic or vaccine characteristics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".