Effectiveness of Canadian travel restrictions in reducing burden of SARS-CoV-2 variants of concern
Bibliographic record
Abstract
Abstract Evaluating travel restriction effectiveness in mitigating infectious disease burden is critical for informing public health policy. Here, we quantify where and when variants of SARS-CoV-2 were introduced into Canada to evaluate the extent to which travel restrictions averted viral introductions and COVID-19 case burden. Our results suggest that, across SARS-CoV-2 variants of concern subject to travel restrictions, at least 281 introductions were prevented, accounting for an averted burden of approximately 44,064 cases. This corresponds to approximately 441 averted hospitalizations, 24 averted deaths, and cost savings to Canadian health care systems of approximately 11.2 million Canadian dollars. Travel restrictions were found to be most effective when implemented rapidly during exponential case growth in the focal source and when global circulation was limited. Our analyses reveal that COVID-19 travel restrictions mitigated case burdens and highlight their value in future pandemic response. Summary COVID-19 travel restrictions against variants worked and were most effective when implemented rapidly and preceding new variants’ wider circulation.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".