Impact of an Immunization Campaign to Control an Increased Incidence of Serogroup B Meningococcal Disease in One Region of Quebec, Canada
Bibliographic record
Abstract
Background: Invasive meningococcal disease (IMD) incidence increased in Quebec, starting in 2003, and was caused by a serogroup B sequence type 269 clone. The Saguenay-Lac-Saint-Jean (SLSJ) region was particularly affected with a rate of 3.4 per 100000 person-years in 2006-2013. In May 2014, an immunization campaign was launched in SLSJ, using the 4-component protein-based meningococcal vaccine (MenB-4C). We aimed to evaluate the impact of the campaign 2 years after its initiation. Methods: Immunization registry data and serogroup B invasive meningococcal disease (B-IMD) cases notified to public health authorities and confirmed by culture or polymerase chain reaction from July 1996 to December 2016 were analyzed, including a multivariate Poisson regression model of incidence rates. Results: By the end of the campaign, 82% of the 59000 targeted SLSJ residents between 2 months and 20 years of age had been immunized. Following the initiation of the campaign, no B-IMD case occurred among vaccinees, whereas 2 cases were reported among unvaccinated adult SLSJ residents, and a third case in an unvaccinated child who had stayed in the region during the week prior to disease onset, in 2015. B-IMD incidence decreased in all other regions in the years 2015-2016 but sporadic cases continued to occur. A multivariate analysis showed a significant effect of the campaign in the SLSJ region (relative B-IMD risk: 0.22; P = .04). Conclusions: Results suggest a high level of protection provided by MenB-4C following mass vaccination at regional level. This, along with reassuring safety data, supports the current recommendations for MenB-4C use for controlling outbreaks caused by clones covered by the vaccine.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".