Age, influenza pandemics and disease dynamics
Bibliographic record
Abstract
The world is currently confronting the first influenza pandemic of the 21st century [caused by a novel pandemic influenza A (H1N1) virus]. Earlier pandemics have been characterized by age distributions that are distinct from those observed with seasonal influenza epidemics, with higher attack rates (and correspondingly increased proportionate or relative mortality) in younger individuals. While the genesis of protection against infection in older individuals during a pandemic is uncertain, differential vulnerability to infection by age has important implications for disease dynamics and control, and for choice of optimal vaccination strategies. Age-related vulnerability to infection may explain differences between school- and community-derived estimates of the reproductive number (R) for a newly emerged pandemic strain, and may also help explain the failure of a newly emerged influenza A (H1N1) virus strain to cause a pandemic in 1977. Age-related factors may also help explain variability in attack rates, and the size and impact of influenza epidemics across jurisdictions and between populations. In Canada, such effects have been observed in the apparently increased severity of outbreaks on Indigenous peoples' reserves. The implications of these patterns for vaccine allocation necessitate targeted research to understand age-related vulnerabilities early in an influenza pandemic.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".