Facial Protective Equipment, Personnel, and Pandemics: Impact of the Pandemic (H1N1) 2009 Virus on Personnel and Use of Facial Protective Equipment
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Before the emergence of the pandemic (H1N1) 2009 virus, estimates of the stockpiles of facial protective equipment (FPE) and the impact that information had on personnel during a pandemic varied. OBJECTIVE: To describe the impact of H1N1 on FPE use and hospital employee absenteeism. Setting. One tertiary care hospital and 2 community hospitals in the Vancouver Coastal Health (VCH) region, Vancouver, Canada. Patients. All persons with influenza-like illness admitted to the 3 VCH facilities during the period from June 28 through December 19, 2009. METHODS: Data on patients and on FPE use were recorded prospectively. Data on salaried employee absenteeism were recorded during the period from August 1 through December 19, 2009. RESULTS: During the study period, 865 patients with influenza-like illness were admitted to the 3 VCH facilities. Of these patients, 149 (17.2%) had laboratory-confirmed H1N1 influenza infection. The mean duration of hospital stay for these patients was 8.9 days, and the mean duration of intensive care unit stay was 9.2 days. A total of 134,281 masks and 173,145 N95 respirators (hereafter referred to as respirators) were used during the 24-week epidemic, double the weekly use of both items, compared with the previous influenza season. A ratio of 3 masks to 4 respirators was observed. Use of disposable eyewear doubled. Absenteeism mirrored the community epidemiologic curve, with a 260% increase in sick calls at the epidemic peak, compared with the nadir. CONCLUSION: Overall, FPE use more than doubled, compared with the previous influenza season, with respirator use exceeding literature estimates. A significant proportion of FPE resources were used while managing suspected cases. Planners should prepare for at least a doubling in mask and respirator use, and a 3.6-fold increase in staff sick calls.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it