2285. Using Genomic Sequencing to Describe SARS-CoV-2 Transmission Dynamics in U.S. Major League Soccer Clubs
Bibliographic record
Abstract
Abstract Background In 2020–2022, U.S. Major League Soccer (MLS) used SARS-CoV-2 mitigation protocols that included masking, social distancing, avoiding contact with others outside of training and games, testing, quarantine, and isolation. In addition to isolation for those who tested positive, a SARS-CoV-2 genomic sequencing strategy was developed to identify whether infections were associated with intra-league transmission. Methods Nasopharyngeal swabs were collected by MLS club medical staff from players and staff from February 2021 through September 2022. During this time, surveillance testing changed from daily to weekly to testing only symptomatic players and staff. SARS-CoV-2 positive samples were analyzed using amplicon-based whole genome sequencing. A phylogenetic tree was constructed using Nextstrain to visualize genomes from infected players and staff in the context of genomes available on GISAID circulating in the United States during corresponding time periods. To identify transmission links, all genomes were compared in a pairwise fashion. Genomes that were 0–2 nucleotides different were considered part of direct transmission clusters. Results Of 250 samples that were rtPCR positive for SARS-CoV-2, 215 (86%) were sequenced. Phylogenetic analysis showed a broad diversity of lineages, including some predominant overseas (e.g., AY.98.1). Pairwise comparison revealed SARS-CoV-2 sequences from 7 individuals appeared to be linked. These individuals were on 2 different MLS teams; there was an off-field exposure (dinner). Five (71%) had identical SARS-CoV-2 sequences; 2 had sequences that were 1 nucleotide different at the consensus level. Subconsensus genome analysis revealed that differences of 1 nucleotide were due to subconsensus mutations fluctuating below and above 50%, suggesting all 7 individuals were part of a transmission cluster. Phylogenetic analysis revealed that the sequences from the cluster were distinct from reference sequences and were likely a unique transmission chain. Conclusion SARS-CoV-2 transmission may occur within, and even between, professional sports teams. Pairwise comparison of individual genomes can provide improved granularity to identify clusters and understand SARS-CoV-2 transmission. Disclosures Davidson H. Hamer, MD, Kephera Diagnostics: Grant/Research Support|Takeda: Advisor/Consultant|Takeda: Grant/Research Support|Trinity Biotech, LLC: Advisor/Consultant|Valneva: Advisor/Consultant|Valneva: Grant/Research Support Daniel Bourque, MD, Kephera Diagnostics: Grant/Research Support
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".