Detection of the novel SARS-CoV-2 European lineage B.1.177 in Ontario, Canada
Bibliographic record
Abstract
Background: Travel-related dissemination of SARS-CoV-2 continues to contribute to the global pandemic. A novel SARS-CoV-2 lineage (B.1.177) reportedly arose in Spain in the summer of 2020, with subsequent spread across Europe linked to travel by infected individuals. Surveillance and monitoring through the use of whole genome sequencing (WGS) offers insights into the global and local movement of pathogens such as SARS-CoV-2 and can detect introductions of novel variants. Methods: We analysed the genomes of SARS-CoV-2 sequenced for surveillance purposes from specimens received by Public Health Ontario (Sept 6 - Oct 10, 2020), collected from individuals in eastern Ontario, which comprised the study sample. Taxonomic lineages were identified using pangolin (v2.08) and phylogenetic analysis incorporated publicly available genomes covering the same time period as the study sample. Epidemiological data collected from laboratory requisitions and standard reportable disease case investigation was integrated into the analysis. Results: Genomic surveillance identified a COVID-19 case with SARS-CoV-2 lineage B.1.177 from an individual in eastern Ontario in late September, 2020. The individual had recently returned from Europe. Genomic analysis with publicly available data indicate the most closely related genomes to this specimen were from Southern Europe. Genomic surveillance did not identify further cases with this lineage. Conclusions: Genomic surveillance allowed for early detection of a novel SARS-CoV-2 lineage in Ontario which was deemed to be travel related. This type of genomic-based surveillance is a key tool to measure the effectiveness of public health measures such as mandatory self-isolation for returned travellers, aimed at preventing onward transmission of newly introduced lineages of SARS-CoV-2.
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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 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".