Transmissibility of the 2009 H1N1 pandemic in remote and isolated Canadian communities: a modelling study
Bibliographic record
Abstract
OBJECTIVES: During the first wave of the 2009 influenza pH1N1, disease burden was distributed in a geographically heterogeneous fashion. It was particularly high in some remote and isolated Canadian communities when compared with urban centres. We sought to estimate the transmissibility (the basic reproduction number) of pH1N1 strain in some remote and isolated Canadian communities. DESIGN: A discrete time susceptible-exposed-infected transmission model was fit to infection curves simulated from laboratory-confirmed case counts for pH1N1 on each day. The sampling from Poisson distribution was used to estimate the basic reproduction number, R(0), of pH1N1 during the spring wave for five different communities in Manitoba and Nunavut, Canada, where remote and isolated communities experienced a high incidence of infection, and high rates of hospitalisation and intensive care unit admission. SETTING: Remote and isolated communities in Northern Manitoba, Nunavut, and the largest urban centre (Winnipeg) in the province of Manitoba, Canada. RESULTS: Using published values of the exposed and infectious periods specific to H1N1 infection, corresponding to the average generation time of 2.78 days, we estimated a mean value of 2.26 for R(0) (95% CI 1.57 to 3.75) in a community located in northern Manitoba. Estimates of R(0) for other communities in Nunavut varied considerably with higher mean values of 3.91 (95% CI 3.08 to 4.87); 2.03 (95% CI 1.50 to 3.19); and 2.45 (95% CI 1.68 to 3.44). We estimated a lower mean value of 1.57 (95% CI 1.35 to 1.87) for R(0) in the Winnipeg health region, as the largest urban centre in Manitoba. CONCLUSIONS: Influenza pH1N1 appears to have been far more transmissible in rural and isolated Canadian communities than other large urban areas. The differential severity of the pandemic in these regions may be explained partly by differential transmissibility, and suggests the need for more nuanced, targeted or population-specific control strategies in Canada.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".