Association Between Seasonal Respiratory Virus Activity and Invasive Pneumococcal Disease in Central Ontario, Canada
Bibliographic record
Abstract
ABSTRACT Background In central Ontario, influenza, respiratory syncytial virus (RSV), and invasive pneumococcal disease (IPD) follow similar seasonal patterns, peaking in winter. We aimed to quantify the independent and joint impact of influenza A, influenza B, and RSV on IPD risk at the population level. Methods We used a 2:1 self-matched case-crossover study design to evaluate acute effects of respiratory virus activity on IPD risk. This design ensures that effects are not confounded by within-individual characteristics that remain constant over short periods of time. We included 3,892 IPD cases occurring between January 2000 and June 2009. Effects were measured using univariable and multivariable conditional logistic regression. Multivariable models included environmental covariates (e.g., temperature, absolute humidity, and UV index) and interaction terms between viruses. Results Influenza A activity and influenza B activity were both independently associated with increased IPD risk; however, co-circulation of influenza A and B reduced the impact of both viruses. RSV activity was positively associated with increased IPD risk only in the presence of increased influenza A or influenza B activity. Conclusions To our knowledge this represents the first study to consider the impact of interactions between these viruses on IPD risk in Canada. Our findings suggest that the prevention of IPD should be considered as a potential health benefit of influenza and RSV vaccination programs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".