Relative risks of COVID-19 fatality between the first and second waves of the pandemic in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVES: To examine whether the case fatality rate (CFR) of COVID-19 decreased over time and whether the COVID-19 testing rate is a driving factor for the changes if the CFR decreased. METHODS: Analyzing COVID-19 cases, deaths and tests in Ontario, Canada, we compared the CFR between the first wave and the second wave across 26 public health units in Ontario. We also explored whether a high testing rate was associated with a large CFR decrease. RESULTS: The first wave CFR ranged from 0.004 to 0.146, whereas the second wave CFR ranged from 0.003 to 0.034. The pooled RR estimate of second wave COVID-19 case fatality, compared with first wave, was 0.24 (95% CI: 0.19-0.32). Additionally, COVID-19 testing percentages were not associated with the estimated relative risk (P=0.246). CONCLUSIONS: The COVID-19 CFR decreased significantly in Ontario during the second wave, and COVID-19 testing was not a driving factor for this decrease.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".