Influence of School Year on Seasonality of Norovirus Outbreaks in Developed Countries
Bibliographic record
Abstract
Factors affecting the seasonal distribution of norovirus outbreaks are not well understood. This study examined whether grade school settings at the start of the school year may be a factor. We searched Ovid Medline from January 2002 to June 2014 for studies that provided all reported norovirus outbreaks in a developed country by month for a minimum of three years. Historical school years were obtained from verifiable sources. The start of the norovirus seasonal outbreak peak and peak outbreak month were determined for each study and compared to the start month of school. Northern hemisphere and southern hemisphere countries had a different norovirus seasonality and different school year structures (traditional compared to year round). In the two studies that provided outbreaks by age, outbreaks among children started several months before outbreaks in the adult population. The median number of months between school start and start of the seasonal outbreak peak was two months (interquartile range [IQR] = 2.0-3.0), while the median number of months between school start and peak outbreak month was four months (IQR = 3.0-4.0). These findings suggest the possibility the school setting at the start of the school year may be a factor in the seasonality of norovirus.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".