The Geographic Synchrony of Seasonal Influenza: A Waves across Canada and the United States
Bibliographic record
Abstract
BACKGROUND: As observed during the 2009 pandemic, a novel influenza virus can spread globally before the epidemic peaks locally. As consistencies in the relative timing and direction of spread could form the basis for an early alert system, the objectives of this study were to use the case-based reporting system for laboratory confirmed influenza from the Canadian FluWatch surveillance program to identify the geographic scale at which spatial synchrony exists and then to describe the geographic patterns of influenza A virus across Canada and in relationship to activity in the United States (US). METHODOLOGY/PRINCIPAL FINDINGS: Weekly laboratory confirmations for influenza A were obtained from the Canadian FluWatch and the US FluView surveillance programs from 1997/98 to 2006/07. For the six seasons where at least 80% of the specimens were antigenically similar, we identified the epidemic midpoint of the local/regional/provincial epidemics and analyzed trends in the direction of spread. In three out of the six seasons, the epidemic appeared first in Canada. Regional epidemics were more closely synchronized across the US (3-5 weeks) compared to Canada (5-13 weeks), with a slight gradient in timing from the southwest regions in the US to northeast regions of Canada and the US. Cities, as well as rural areas within provinces, usually peaked within a couple of weeks of each other. The anticipated delay in peak activity between large cities and rural areas was not observed. In some mixed influenza A seasons, lack of synchronization sub-provincially was evident. CONCLUSIONS/SIGNIFICANCE: As mixing between regions appears to be too weak to force a consistency in the direction and timing of spread, local laboratory-based surveillance is needed to accurately assess the level of influenza activity in the community. In comparison, mixing between urban communities and adjacent rural areas, and between some communities, may be sufficient to force synchronization.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".