The Number Needed to Vaccinate to Prevent Infant Pertussis Hospitalization and Death Through Parent Cocoon Immunization
Bibliographic record
Abstract
BACKGROUND: Parental immunization has been recommended as a "cocoon" strategy to prevent serious pertussis outcomes in early infancy. We illustrate the high number needed to vaccinate (NNV) for this program based on recent epidemiologic data from the provinces of Québec and British Columbia (BC), Canada. METHODS: Surveillance trends were summarized for the period 1990-2010. Hospitalization, intensive care unit (ICU) admission, and mortality data were compiled from 2000 to 2009. The proportion of infant pertussis attributed to a parent was estimated at 35%, explored up to 55%. Adult vaccine efficacy (VE) was estimated at 85%. The NNV was calculated as [2 parents/(parent-attributable infant risk × parent VE)]. To capture at least 1 recent cyclical peak, NNV was derived for the period 2005-2009 and explored for peak/trough years. RESULTS: Substantial decline has occurred in pertussis incidence across all age groups including infants, reaching a 20-year nadir in 2010 in both provinces. For the period 2005-2009, the risk of infant hospitalization and ICU admission was 57 and 7, respectively, per 100 000 in Québec and 33 and 7, respectively, per 100 000 in BC. In both provinces the risk of infant pertussis-related death over that period was <0.5 per 100 000. The NNV for parental immunization was at least 1 million to prevent 1 infant death, approximately 100 000 for ICU admission, and >10 000 for hospitalization. CONCLUSIONS: In the context of low pertussis incidence, the parental cocoon program is inefficient and resource intensive for the prevention of serious outcomes in early infancy. Regions contemplating the cocoon program should consider the NNV based on local epidemiology.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".