Pertussis resurgence in Canada largely caused by a cohort effect
Bibliographic record
Abstract
BACKGROUND: Beginning in 1990 Canada experienced a resurgence of pertussis. Changes in incidence and hospitalization according to age in the province of Quebec between 1983 and 1998 were examined to assess the presence of a cohort effect resulting from a poorly protective vaccine. METHODS: The source of data on incident cases was pertussis notifications to the Quebec Ministry of Health and Social Services. Hospitalization data were extracted from the administrative database that collects information on each hospitalization. RESULTS: The mean annual incidence before 1990 was 3.8 cases per 100,000 population which increased to 37.2 thereafter. Infants had the smallest increase (2.7-fold) when compared with children between 1 and 19 years who experienced a 9- to 15-fold increase and with adults (22.5-fold). The mean annual hospitalization rates increased from 2.7 per 100,000 before 1990 to 5.2 afterward. Ninety percent of hospitalizations occurred in children <5 years of age. The proportion of cases in 0- to 4-year-old children decreased, whereas it increased steadily in all other age groups during the entire study period. Between 1990 and 1998 the median age of cases shifted from 4.4 to 7.8 years. Pertussis affected predominantly children who were immunized with a vaccine introduced in the mid-1980s. The evolution of the age distribution of cases paralleled the aging of this cohort with a slow but steady drift of disease from early childhood to adolescence. CONCLUSION: The sudden increase in pertussis incidence in Canada can be largely attributed to a cohort effect resulting from a poorly protective pertussis vaccine used between 1985 and 1998.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".