Summary of the NACI Seasonal Influenza Vaccine Statement for 2020–2021
Bibliographic record
Abstract
BACKGROUND: Evidence on influenza vaccination is continually evolving. The National Advisory Committee on Immunization (NACI) provides annual recommendations to the Public Health Agency of Canada regarding the use of seasonal influenza vaccines. OBJECTIVE: To summarize NACI's recommendations regarding the use of seasonal influenza vaccines for the 2020-2021 influenza season and to highlight new and updated recommendations. METHODS: 1) To update wording on influenza vaccination of health care workers, NACI reassessed the evidence in the context of ethics and acceptability frameworks, in accordance with NACI's recently expanded mandate. 2) To provide recommendations on the use of live attenuated influenza vaccine (LAIV) in HIV-infected individuals, the Influenza Working Group developed a predefined search strategy to identify all eligible studies, then assessed the quality and summarized and analyzed the findings according to the NACI evidence-based process. NACI provided new recommendations based on assessment of the evidence. RESULTS: 1) NACI continues to recommend that health care workers and other care providers in facilities and community settings should be vaccinated annually against influenza and that this group be included among those particularly recommended to receive the influenza vaccine. 2) NACI concluded that LAIV is immunogenic in children with stable HIV infection; therefore, NACI newly recommends that LAIV may be considered as an option for children 2-17 years of age with stable HIV infection on highly active antiretroviral therapy and with adequate immune function. CONCLUSION: NACI continues to recommend that an age-appropriate influenza vaccine should be offered annually to anyone six months of age and older who does not have contraindications to the vaccine, with a focus on the groups for whom influenza vaccination is particularly recommended.
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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 | 0.028 | 0.053 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.027 | 0.025 |
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".