In-person schooling and COVID-19 transmission in Canada’s three largest cities
Bibliographic record
Abstract
ABSTRACT In North America and Europe, the Fall 2020 school term has coincided with the beginning of the second wave of the novel coronavirus (COVID-19) pandemic, sparking a heated debate about the role of in-person schooling for community transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This issue has immediate policy relevance for deciding how to operate schools safely as the pandemic unfolds, new variants of SARS-CoV-2 are circulating, and immunization coverage remains low. We contribute to this debate by presenting data on trends in COVID-19 weekly incidence among school-aged children 0-19 years old vis-à-vis other age groups during Fall 2020 in Canada’s three largest cities: Montréal, Toronto and Calgary. We interpret these trends in light of the different back-to-school policies and other public health measures implemented in the three cities over the observation period. KEY POINTS School closures are an effective measure to reduce the overall incidence of the novel coronavirus (COVID-19). Nonetheless, there is a general consensus that the decision to close schools to control the spread of COVID-19 should be used as last resort because of the negative impact on children’s development and mental health, and since they are less likely to have severe COVID-19 outcomes than adults. Existing evidence highlights the importance of adopting appropriate mitigation strategies for limiting COVID-19 community spread when returning to in-person schooling. To understand the association between in-person schooling and COVID-19 transmission given different mitigation strategies, especially universal masking and distance learning, we compare how the second wave of COVID-19 has affected school-aged children age 0-19 years old vis-à-vis other age groups in Montréal, Toronto and Calgary during Fall 2020. The case of Montréal attests to the negative consequences of not implementing recommended migration strategies when reopening schools, even when public health measures such as gatherings restrictions are in place to maintain low levels of community transmission. On the contrary, school measures adopted in Toronto (optional distance learning and masking mandates), have limited the role of COVID-19 transmission among school-aged children for overall community transmission. In Calgary, this effect has been smaller, likely because public health measures to limit COVID-19 community spread were not introduced until early December 2020. Our findings have immediate policy relevance for deciding how to operate schools safely as the pandemic unfolds, new variants of SARS-CoV-2 are circulating, and immunization coverage remains low.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".