Chasing the origin of SARS-CoV-2 in Canada’s COVID-19 cases: A genomics study
Bibliographic record
Abstract
Abstract The emergence and global spread of SARS-CoV-2 has had profound social and economic consequences and has shed light on the importance of continued and additional investment in global health and infectious disease surveillance. Identifying changes in viral genomes provides key insights into viral diversity, how viruses spread within populations, and viral strategies for evasion of host immune systems. Here we report twenty-five SARS-CoV-2 genome sequences collected from some of the first COVID-19 cases in eastern Ontario, Canada (March 18-30, 2020). The reported genomes belong to the S-clade ( n =2) and G-clade ( n =23) of SARS-CoV-2 and contain 45 polymorphic sites including one shared missense and three unique synonymous variants in the gene encoding the spike protein. A phylogenetic analysis enabled the tracing of viral origin and potential transmission into and within Canada. There may be as many as sixteen unique infection events represented in these samples, including at least three that were likely introduced from Europe and seven from the USA. In addition, four separate genomes are each shared by multiple patients, suggesting a common origin or community spread even during this early stage of infection. These results demonstrate how molecular epidemiology and evolutionary phylogenetics can help local health units track origins and vectors of spread for emerging diseases like SARS-CoV-2. Earlier detection and screening in this way could improve the effectiveness of regional public health interventions to prevent future pandemics.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 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) | 0.001 | 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".