Estimates of Influenza Vaccine Effectiveness for 2007–2008 From Canada's Sentinel Surveillance System: Cross-Protection Against Major and Minor Variants
Bibliographic record
Abstract
OBJECTIVES: To estimate influenza vaccine effectiveness (VE) for the 2007-2008 season and assess the sentinel surveillance system in Canada for monitoring virus evolution and impact on VE. METHODS: Nasal/nasopharyngeal swabs and epidemiologic details were collected from patients presenting to a sentinel physician within 7 days of influenza-like illness onset. Cases tested positive for influenza A/B virus by real-time polymerase chain reaction; controls tested negative. Hemagglutination inhibition (HI) and gene sequencing explored virus relatedness to vaccine. VE was calculated as 1 minus the odds ratio for influenza in vaccinated versus nonvaccinated participants, with adjustment for confounders. RESULTS: Of 1425 participants, 21% were vaccinated. Influenza virus was detected in 689 (48%), of which isolates from 663 were typed/subtyped: 189 (29%) were A/H1, 210 (32%) were A/H3, and 264 (40%) were B. Of A/H1N1 isolates, 6% showed minor HI antigenic mismatch to vaccine, with greater variation based on genetic identity. All A/H3N2 isolates showed moderate antigenic mismatch, and 98% of influenza B virus isolates showed major lineage-level mismatch to vaccine. Adjusted VE for A/H1N1, A/H3N2, and B components was 69% (95% confidence interval [CI], 44%-83%), 57% (95% CI, 32%-73%), and 55% (95% CI, 32%-70%), respectively, with an overall VE of 60% (95% CI, 45%-71%). CONCLUSIONS: Detailed antigenic and genotypic analysis of influenza viruses was consistent with epidemiologic estimates of VE showing cross-protection. A routine sentinel surveillance system that combines detailed virus and VE monitoring annually, as modeled in Canada, may guide improved vaccine selection and protection.
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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 | 0.001 | 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".