Respiratory tract samples collected from patients in a region of Quebec, Canada, indicate the absence of early circulation of SARS-CoV-2 infection
Bibliographic record
Abstract
Background: The first documented case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Quebec was confirmed on February 27, 2020. Retracing the first cases that occur within a geographical region may provide insight regarding the evolution and spread of SARS-CoV-2 in that region because the spread of undiagnosed cases may facilitate the initial community amplification of the virus. Methods: We performed a retrospective analysis of respiratory tract samples collected for influenza testing in a region of Quebec, Canada, to look for evidence of early circulation of SARS-CoV-2. Frozen nucleic acid extracts initially collected for influenza testing between January 1 and February 20, 2020, were tested for SARS-CoV-2 using a reverse transcription-polymerase chain reaction assay. Results: During the study period, 1,440 of 2,121 (67.9%) nucleic acid extracts from individual patients were available for retrospective testing. None of the samples tested positive for SARS-CoV-2. Conclusions: The results suggest that SARS-CoV-2 was not circulating within the region before February 20, 2020, because many samples, representing more than two-thirds of all samples tested for influenza during early 2020, were tested. Further studies using a similar methodology to determine the date of onset of SARS-CoV-2 in different countries and geographic areas could enhance our understanding of the current pandemic.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".