Measles Antibody Levels in Young Infants
Bibliographic record
Abstract
BACKGROUND: Infants are often assumed to be immune to measles through maternal antibodies transferred during pregnancy and, in many countries, receive their first measles-containing vaccine at 12 to 15 months. Immunity may wane before this time in measles-eliminated settings, placing infants at risk for measles and complications. We investigated humoral immunity to measles in infants <12 months of age in Ontario, Canada. METHODS: We selected sera collected at a tertiary pediatric hospital from infants <12 months who were born at ≥37 weeks' gestational age. We excluded infants with conditions that affect antibody levels. We selected ≤25 sera from 8 predetermined age bands and tested them for measles-neutralizing antibody using the plaque-reduction neutralization test. We calculated the proportion immune at each age band, and predictors of infant susceptibility were assessed by using multivariable logistic regression and Poisson regression. RESULTS: Of 196 infant sera, 56% (110 of 196) were from boys, and 35% (69 of 196) were from infants with underlying medical conditions. In the first month, 20% (5 of 25) of infants had antibodies below the protective threshold, which increased to 92% (22 of 24) by 3 months. By 6 months, all infants had titers below the protective threshold. In a multivariable analysis, infant age was the strongest predictor of susceptibility (odds ratio = 2.13 for each additional month increase; 95% confidence interval: 1.52-2.97). CONCLUSIONS: Most infants were susceptible to measles by 3 months of age in this elimination setting. Our findings inform important policy discussions relating to the timing of the first dose of measles-containing vaccine and infant postexposure prophylaxis recommendations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".