Transmission dynamics and risk factors for pandemic H1N1‐related illness: outbreak investigation in a rural community of British Columbia, Canada
Bibliographic record
Abstract
OBJECTIVE: To characterize the first-wave epidemiologic features of influenza-like illness (ILI) associated with the novel pandemic A/H1N1 [A(H1N1)pdm09] virus. METHODS: We used generalized linear mixed models (GLMM) to assess risk factors and non-parametric and/or parametric distributions to estimate attack rates, secondary attack rates (SAR), duration of illness, and serial interval during a laboratory-confirmed community outbreak of A(H1N1)pdm09 clustered around on-reserve residents and households of an elementary school in rural British Columbia, Canada, in late April/early May 2009. ILI details were collected as part of outbreak investigation by community telephone survey in early June 2009. RESULTS: Overall, 92/408 (23%) of participants developed ILI and 36/408 (9%) experienced medically attended ILI (MAILI). The overall SAR in households was 22%: highest among participants 1-4 years of age (yoa) (50%) followed by < 1 yoa (38%), 5-8 yoa (20%), 10-19 yoa (13%), 20-49 yoa (20%), and 50-64 yoa (0%). The median serial interval was estimated at 3·5 days (95% CI: 2·1-5·1). In multivariable GLMM analysis, having a chronic condition (OR: 2·58; 95% CI: 1·1-6·04), younger age [1-8 yoa: OR: 4·63; 95% CI: 2·25-9·52; 9-19 yoa: OR: 1·95; 95% CI: 0·97-3·9 (referent: ≥ 20 yoa)] and receipt of 2008-2009 influenza vaccine (OR: 2·68; 95% CI: 1·37-5·25) were associated with increased risk of ILI. Median duration of illness was 9 days, longer among those with chronic conditions (21 days). Median time to seeking care after developing illness was 4·5 days. On-reserve participants had higher chronic conditions, household density, ILI, MAILI, and SAR. CONCLUSIONS: During a community outbreak of A(H1N1)pdm09-related illness, we identified substantial clinical ILI attack rates exceeding 20% with secondary household attack rates as high as 50% in young children. The serial interval was short suggesting a narrow period to prevent transmission.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".