SARS-CoV-2 and the role of airborne transmission: a systematic review
Bibliographic record
Abstract
Background: Airborne transmission is the spread of an infectious agent caused by the dissemination of droplet nuclei (aerosols) that remain infectious when suspended in the air. We carried out a systematic review to identify, appraise and summarise the evidence from studies of the role of airborne transmission of SARS-CoV-2. Methods: We searched LitCovid, MedRxiv, Google Scholar and the WHO Covid-19 database from 1 February to 20 December 2020 and included studies on airborne transmission. Data were dual extracted and we assessed quality using a modified QUADAS 2 risk of bias tool. Results: We included 67 primary studies and 22 reviews on airborne SARS-CoV-2. Of the 67 primary studies, 53 (79%) reported data on RT-PCR from air samples, 12 (18%) report cycle threshold values and 18 (127%) copies per sample volume. All primary studies were observational and of low quality. The research often lacked standard methods, standard sampling sizes and reporting items. We found 36 descriptions of different air samplers deployed. Of the 42 studies conducted in-hospital that reported binary RT-PCR tests, 24 (57%) reported positive results for SARs-CoV-2 (142 positives out of 1,403 samples: average 10.1%, range 0% to 100%). There was no pattern between the type of hospital setting (ICU versus non-ICU) and RT-PCR positivity. Seventeen studies reported potential air transmission in the outdoors or in the community, of which seven performed RT-PCR sampling, and two studies reported weak positive RNA samples for 2 or more genes (5 of 125 samples positive: average 4.0%). Ten studies attempted viral culture with no serial passage. Conclusion: SARS-CoV-2 RNA is detected intermittently in the air in various settings. Standardized guidelines for conducting and reporting research on airborne transmission are needed. The lack of recoverable viral culture samples of SARS-CoV-2 prevents firm conclusions from being drawn about airborne transmission.
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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 | 0.013 | 0.071 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".