LESSONS FROM THE COVID-19 THIRD WAVE IN CANADA: THE IMPACT OF VARIANTS OF CONCERN AND SHIFTING DEMOGRAPHICS
Bibliographic record
Abstract
ABSTRACT Importance With the emergence of more transmissible SARS-CoV-2 variants of concern (VOC), there is an urgent need for evidence about disease severity and the health care impacts of VOC in North America, particularly since a substantial proportion of the population have declined vaccination thus far. Objective To examine 30-day outcomes in Canadians infected with SARS-CoV-2 in the first year of the pandemic and to compare event rates in those with VOC versus wild-type infection. Design Retrospective cohort study using linked healthcare administrative datasets. Setting Alberta and Ontario, the two Canadian provinces that experienced the largest third wave in the spring of 2021. Participants All individuals with a positive SARS-CoV-2 reverse transcriptase polymerase chain reaction swab from March 1, 2020 until March 31, 2021, with genomic confirmation of VOC screen-positive tests during February and March 2021 (wave 3). Exposure of Interest VOC versus wild type SARS-CoV-2 Main Outcomes and Measures All-cause hospitalizations or death within 30 days after a positive SARS-CoV-2 swab. Results Compared to the 372,741 individuals with SARS-CoV-2 infection between March 2020 and January 2021 (waves 1 and 2 in Canada), there was a shift in transmission towards younger patients in the 104,232 COVID-19 cases identified in wave 3. As a result, although third wave patients were more likely to be hospitalized (aOR 1.34 [1.29-1.39] in Ontario and aOR 1.53 [95%CI 1.41-1.65] in Alberta), they had shorter lengths of stay (median 5 vs. 7 days, p<0.001) and were less likely to die within 30 days (aOR 0.66 [0.60-0.71] in Ontario and aOR 0.74 [0.62-0.89] in Alberta). However, within the third wave, patients infected with VOC (91% Alpha) exhibited higher risks of death (aOR 1.52 [1.27-1.81] in Ontario and aOR 1.67 [1.13-2.48] in Alberta) and hospitalization (aOR 1.57 [1.47-1.69] in Ontario and aOR 1.88 [1.74-2.02] in Alberta) than those with wild-type SARS-CoV-2 infections during the same timeframe. Conclusions and Relevance On a population basis, the shift towards younger age groups as the COVID-19 pandemic has evolved translates into more hospitalizations but shorter lengths of stay and lower mortality risk than seen in the first 10 months of the pandemic in Canada. However, on an individual basis, infection with a VOC is associated with a higher risk of hospitalization or death than the original wild-type SARS-CoV-2 – this is important information to address vaccine hesitancy given the increasing frequency of VOC infections now.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".