Detection of SARS-CoV-2 in saliva: implications for specimen transport and storage
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Saliva has recently been proposed as a suitable specimen for the diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Use of saliva as a diagnostic specimen may present opportunities for SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) testing in remote and low-resource settings. Determining the stability of SARS-CoV-2 RNA in saliva over time is an important step in determining optimal storage and transport times. We undertook an in vitro study to assess whether SARS-CoV-2 could be detected in contrived saliva samples. The contrived saliva samples comprised 10 ml pooled saliva spiked with gamma-irradiated SARS-CoV-2 to achieve a concentration of 2.58×10 4 copies ml SARS-CoV-2, which was subsequently divided into 2 ml aliquots comprising: (i) neat saliva; and a 1 : 1 dilution with (ii) normal saline; (iii) viral transport media, and (iv) liquid Amies medium. Contrived samples were made in quadruplicate, with two samples of each stored at either: (i) room temperature or (ii) 4 °C. SARS-CoV-2 was detected in all SARS-CoV-2 spiked samples at time point 0, day 1, 3 and 7 at both storage temperatures using the N gene RT-PCR assay and time point 0, day 1 and day 7 using the Xpert Xpress SARS-CoV-2 (Cepheid, Sunnyvale, USA) RT-PCR assay. The ability to detect SARS-CoV-2 in saliva over a 1 week period is an important finding that presents further opportunities for saliva testing as a diagnostic specimen for the diagnosis of SARS-CoV-2.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it