Invasive bacterial infections following influenza: a time‐series analysis in Montréal, Canada, 1996–2008
Bibliographic record
Abstract
BACKGROUND: Shared seasonal patterns, such as between influenza and some respiratory bacterial infections, can create associations between phenomena not causally related. OBJECTIVES: To estimate the association of influenza with subsequent bacterial infections after full adjustment for confounding by seasonal and long-term trends. METHODS: Time series of weekly counts of notified cases of invasive infections with Haemophilus influenzae, Neisseria meningitidis, Streptococcus pneumoniae and Streptococcus pyogenes, in Montréal, Canada, 1996-2008, were modelled by negative binomial regression, with terms representing seasonal and long-term trends and terms for numbers of positive laboratory tests for influenza A and B. RESULTS: The associations of S. pneumoniae, H. influenzae and N. meningitidis with influenza disappeared after seasonal terms were added to the model. However, the influenza B count remained associated with the S. pyogenes counts for the same week and the following week: S. pyogenes incidence rate ratios were 1.0376 (95% CI: 1.0009-1.0757) and 1.0354 (0.9958-1.0766), respectively, for each increase of 1 in the influenza count. CONCLUSIONS: Influenza B accounts for about 8 percnt; of the incidence of invasive S. pyogenes infections, over and above any effect associated with modellable seasonal and long-term trends. This association of influenza B with S. pyogenes infections can be attributed largely to the years 1997, 2001, 2007 and 2008, when late peaks in influenza B counts were followed by peaks in S. pyogenes notifications. This finding reinforces the case for universal immunization against influenza, as partial protection against the 'flesh eating disease'.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".