Canadian national surveys on pandemic influenza preparations: pre-pandemic and peri-pandemic findings
Bibliographic record
Abstract
BACKGROUND: Prior to the 2009 H1N1 Influenza pandemic, public health authorities in Canada and elsewhere prepared for the future outbreak, partly guided by an ethical framework developed within the Canadian Program of Research on Ethics in a Pandemic (CanPREP). We developed a telephone-based survey based on that framework, which was delivered across Canada in late 2008. In June, 2009, the WHO declared pandemic Phase 6 status and from the subsequent October (2009) until May 2010, the CanPREP team fielded a second (revised) survey, collecting another 1,000 opinions from Canadians during a period of pre-pandemic anticipation and peri-pandemic experience. METHODS: Surveys were administered by telephone with random sampling achieved via random digit dialing. Eligible participants were adults, 18 years or older, with per province stratification approximating provincial percentages of national population. Descriptive results were tabulated and logistic regression analyses used to assess whether demographic factors were significantly associated with outcomes, and to identify divergences (between the pre-pandemic and intra-pandemic surveys). RESULTS: N = 1,029 interviews were completed from 1,986 households, yielding a gross response rate of 52% (AAPOR Standard Definition 3). Over 90% of subjects indicated the most important goal of pandemic influenza preparations was saving lives, with 41% indicating that saving lives solely in Canada was the highest priority and 50% indicating saving lives globally was the highest priority. About 90% of respondents supported the obligation of health care workers to report to work and face influenza pandemic risks excepting those with serious health conditions which that increased risks. Strong majorities favoured stocking adequate protective antiviral dosages for all Canadians (92%) and, if effective, influenza vaccinations (95%). Over 70% agreed Canada should provide international assistance to poorer countries for pandemic preparation, even if resources for Canadians were reduced. CONCLUSIONS: Results suggest Canadians trust public health officials to make difficult decisions, providing emphasis is maintained on reciprocity and respect for individual rights. Canadians also support international obligations to help poorer countries and associated efforts to save lives outside the country, even if intra-national efforts are reduced.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".