An Observational Study to Assess the Effectiveness of 4CMenB against Meningococcal Disease and Carriage and Gonorrhea in Adolescents in the Northern Territory, Australia—Study Protocol
Bibliographic record
Abstract
Invasive meningococcal disease (IMD) causes significant morbidity and mortality worldwide with serogroup B being the predominant serogroup in Australia and other countries for the past few decades. The licensed 4CMenB vaccine is effective in preventing meningococcal B disease. Emerging evidence suggests that although 4CMenB impact on carriage is limited, it may be effective against gonorrhoea due to genetic similarities between Neisseria meningitidis and Neisseria gonorrhoeae. This study protocol describes an observational study that will assess the effect of the 4CMenB vaccine against meningococcal carriage, IMD and gonorrhoea among adolescents in the Northern Territory (NT). All 14–19-year-olds residing in the NT with no contraindication for 4CMenB vaccine will be eligible to participate in this cohort study. Following consent, two doses of 4CMenB vaccine will be administered two months apart. An oropharyngeal swab will be collected at baseline and 12 months to detect pharyngeal carriage of Neisseria meningitidis by PCR. The main methodological approaches to assess the effect of 4CMenB involve a nested case control analysis and screening method to assess vaccine effectiveness and an Interrupted Time Series regression analysis to assess vaccine impact. Research ethics approvals have been obtained from Menzies and Central Australian Human Research Ethics Committees and the Western Australian Aboriginal Health Ethics Committee. Results will be provided in culturally appropriate formats for NT remote and regional communities and published in international peer reviewed journals. ClinicalTrials.gov Identifier: NCT04398849.
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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 | 0.012 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".