Whole-cell and acellular pertussis vaccination programs and rates of pertussis among infants and young children
Bibliographic record
Abstract
BACKGROUND: The transition from a whole-cell to a 5-component acellular pertussis vaccine provided a unique opportunity to compare the effect that each type of vaccine had on the incidence of pertussis, under routine conditions, among children less than 10 years of age. METHODS: Analyses were based on passive surveillance data collected between 1995 and 2005. The incidence of pertussis by year and birth cohort was compiled according to age during the surveillance period. We determined the association between vaccine type (whole-cell, acellular or a combination of both) and the incidence of pertussis using Poisson regression analysis after controlling for age (< 1 year, 1-4 years and 5-9 years) and vaccination history (i.e., partial or complete). RESULTS: During 7 of the 11 years surveyed, infants (< 1 year of age) had the highest incidence of pertussis. Among children born after 1997, when acellular vaccines were introduced, the rates of pertussis were highest among infants and preschool children (1-4 years of age). Poisson regression analysis revealed that, in the group given either the whole-cell vaccine or a combination of both vaccines, the incidence of pertussis was lower among infants and preschool children than among school-aged children (5-9 years). The reverse was true in the group given only an acellular vaccine, with a higher incidence among infants and preschool children than among school-aged children. INTERPRETATION: These results suggest that current immunization practices may not be adequate in protecting infants and children less than 5 years of age against pertussis. Altering available acellular formulations or adopting immunization practices used in some European countries may increase the clinical effectiveness of routine pertussis vaccination programs among infants and preschool children.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".