Cross-Border Transmissions of the Delta Substrain AY.29 During Tokyo Olympic and Paralympic Games
Bibliographic record
Abstract
Tokyo Olympic and Paralympic Games, postponed for the COVID-19 pandemic, were finally held in the summer of 2021. Just before the games, the Alpha variant was being replaced with the more contagious Delta variant. AY.4 substrain AY.29, which harbors two additional characteristic mutations of 5239C > T (NSP3 Y840Y) and 5514T > C (NSP3 V932A), emerged in Japan and became dominant in Tokyo by the time of the Olympic Games. Variants of SARS-CoV-2 genomes were performed to extract AY.29 Delta substrain samples with 5239C > T and 5514T > C. Phylogenetic analysis was performed to illustrate how AY.29 strains evolved and were introduced into countries abroad. Simultaneously, ancestral searches were performed for the overseas AY.29 samples to identify their origins in Japan using the maximum variant approach. As of January 10, 2022, 118 samples were identified in 20 countries. Phylogenetic analysis and ancestral searches identified 55 distinct introductions into those countries. The United States had 50 samples with 10 distinct introductions, and the United Kingdom had 13 distinct strains introduced in 18 samples. Other countries or regions with multiple introductions were Canada, Germany, South Korea, Hong Kong, Thailand, and the Philippines. Among the 20 countries, most European and North American countries have vaccination rates over 50% and sufficient genomic surveillances are conducted; transmissions seem contained. However, propagation to unvaccinated regions might have caused unfathomable damages. Since samples in those unvaccinated countries are also undersampled with a longer lead time for data sharing, it will take longer to grasp the whole picture. More rigorous departure screenings for the participants from the unvaccinated countries might have been necessary.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".