Canada’s multi-jurisdictional COVID-19 Public Health response – January to May 2020
Bibliographic record
Abstract
In late January 2020, the first COVID-19 case was reported in Canada. By March 5, 2020, community spread of the virus was identified and by May 26, 2020, close to 86,000 patients had COVID-19 and 6,566 had died. As COVID-19 cases increased, provincial and territorial governments announced states of public health emergency between March 13 and 20, 2020. This paper examines Canada’s public health response to the COVID-19 pandemic during the first four months (January to May 2020) by overviewing the actions undertaken by the federal (national) and regional (provincial/territorial) governments. Canada’s jurisdictional public health structures, public health responses, technological and research endeavours, and public opinion on the pandemic measures are described. As the pandemic unravelled, the federal and provincial/territorial governments unrolled a series of stringent public health interventions and restrictions, including physical distancing and gathering size restrictions; closures of borders, schools, and non-essential businesses and services; cancellations of non-essential medical services; and limitations on visitors in hospital and long-term care facilities. In late May 2020, there was a gradual decrease in the daily numbers of new COVID-19 cases seen across most jurisdictions, which has led the provinces and territories to prepare phased re-opening. Overall, the COVID-19 pandemic in Canada and the substantial amount of formative health and policy-related data being created provide an insight on how to improve responses and better prepare for future health emergencies.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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; both teacher heads agree on what is shown here.
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".