Carriage of <i>Haemophilus influenzae</i> serotype A in children: Canadian Immunization Research Network (CIRN) study
Bibliographic record
Abstract
Background: Haemophilus influenzae serotype a (Hia) has recently emerged as an important cause of invasive disease, mainly affecting young Indigenous children. Carriage of H. influenzae is a pre-requisite for invasive disease and reservoir for transmission. To better understand the epidemiology of invasive Hia disease, we initiated a multicentre study of H. influenzae nasopharyngeal carriage among Canadian children. Methods: With prior parental consent, we collected nasotracheal tubes used during general anaesthesia in healthy children following routine dental surgery in a regional hospital of northwestern Ontario and a dental clinic in central Saskatchewan. In northwestern Ontario, all children were Indigenous (median age 48.0 months, 45.8% female); in Saskatchewan, children were from various ethnic groups (62% Indigenous, median age 56.3 months, 43.4% female). Detection of H. influenzae and serotyping were performed using molecular-genetic methods. Results: A total of 438 nasopharyngeal specimens, 286 in northwestern Ontario and 152 in Saskatchewan were analyzed. Hia was identified in 26 (9.1%) and 8 (5.3%) specimens, respectively. In Saskatchewan, seven out of eight children with Hia carriage were Indigenous. Conclusions: The carriage rates of Hia in healthy children in northwestern Ontario and Saskatchewan are comparable to H. influenzae serotype b (Hib) carriage among Alaska Indigenous children in the pre-Hib-vaccine era. To prevent invasive Hia disease, paediatric conjugate Hia vaccines under development have the potential to reduce carriage of Hia, and thus decrease the risk of transmission and disease among susceptible populations. Addressing the social determinants of health may further eliminate conditions favouring Hia transmission in Indigenous communities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".