Potential Intensive Care unit Ventilator Demand/Capacity Mismatch due to Novel Swine‐Origin H1N1 in Canada
Bibliographic record
Abstract
PURPOSE: To investigate the ability of Canadian intensive care units (ICUs) and ventilators to handle widespread re-emergence of the swine-origin H1N1 virus in the context of an aggressive strategy of vaccination. METHOD: Data collected during the first wave in Winnipeg, Manitoba, were applied to a variety of second wave pandemic models to determine potential ICU and ventilator demand. RESULTS: For attack rates greater than 20% to 25%, significant shortages in ventilators may be expected across Canada regardless of the duration of the pandemic if vaccination is not considered. The shortfall arises largely due to the extended durations that patients must remain on ventilation. From the Winnipeg study, 50% of patients required ventilation for more than two weeks. For larger attack rates of 35%, ventilator demand may exceed capacity for over five weeks, with a peak shortfall of 700 ventilators. Vaccination can significantly reduce the attack rates, and is expected to reduce ventilator demand to manageable levels CONCLUSION: Canada's health care system must be prepared for the possibility of a significant influx of ICU patients during the second wave of swine-origin H1N1. Efficient vaccination and other disease prevention measures can reduce the attack rate to manageable levels.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".