Severe acute respiratory syndrome coronavirus-2 shedding in exhaled material: a systematic review
Bibliographic record
Abstract
This systematic review synthesized evidence on the viral load of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) shedding in exhaled material to understand how the exhaled SARS-CoV-2 viral load of infected individuals varies with days since exposure. Medline, Scopus, and Web of Science databases were searched using a combination of search terms to identify articles that tested exhaled material from SARS-CoV-2 infected patients. Records were systematically screened and assessed for eligibility, following which reference lists of eligible articles were hand-searched to identify further relevant studies. Data extraction and quality assessment of individual studies were conducted prior to synthesizing the evidence. Forty-five articles that sampled exhaled breath, exhaled breath condensate, face masks, and cough samples were reviewed. The variation in the SARS-CoV-2 viral load in these materials was considerable with the detection of viral RNA shed during breathing as far as 43 days after symptom onset. The replication-competent virus was present in all four sample types, with the majority isolated during the first week of symptoms onset. Variations in the sample types and testing protocols precluded meta-analysis. High heterogeneity in exhaled SARS-CoV-2 viral load is likely due to host and viral factors as well as variations in sampling and diagnostic methodologies. Evidence on SARS-CoV-2 shedding in exhaled material is scarce and more controlled fundamental studies are needed to assess this important route of viral shedding.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".