Prevalence of seroprotection against the pandemic (H1N1) virus after the 2009 pandemic
Bibliographic record
Abstract
BACKGROUND: Before pandemic (H1N1) 2009, less than 10% of serum samples collected from all age groups in the Lower Mainland of British Columbia, Canada, showed seroprotection against the pandemic (H1N1) 2009 virus, except those from very elderly people. We reassessed this profile of seroprotection by age in the same region six months after the fall 2009 pandemic and vaccination campaign. METHODS: We evaluated 100 anonymized serum samples per 10-year age group based on convenience sampling. We measured levels of antibody against the pandemic virus by hemagglutination inhibition and microneutralization assays. We assessed geometric mean titres and the proportion of people with seroprotective antibody levels (hemagglutination inhibition titre ≥ 40). We performed sensitivity analyses to evaluate titre thresholds of 80, 20 and 10. RESULTS: Serum samples from 1127 people aged 9 months to 101 years were obtained. The overall age-standardized proportion of people with seroprotective antibody levels was 46%. A U-shaped age distribution was identified regardless of assay or titre threshold applied. Among those less than 20 years old and those 80 years and older, the prevalence of seroprotection was comparably high at about 70%. Seroprotection was 44% among those aged 20-49 and 30% among those 50-79 years. It was lowest among people aged 70-79 years (21%) and highest among those 90 years and older (88%). INTERPRETATION: We measured much higher levels of seroprotection after the 2009 pandemic compared than before the pandemic, with a U-shaped age distribution now evident. These findings, particularly the low levels of seroprotection among people aged 50-79 years, should be confirmed in other settings and closer to the influenza season.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".