Voluntary asymptomatic rapid antigen testing for COVID-19 in staff of inpatient units of an academic mental health hospital
Bibliographic record
Abstract
Background: Significant COVID-19 transmission occurs from people not experiencing symptoms. We aimed to investigate whether rapid antigen testing among pre-symptomatic or asymptomatic healthcare workers along with symptom and exposure screening may help to identify COVID-19 cases. Methods: We invited staff on two inpatient geriatric mental health units to voluntarily undergo testing with the Abbott PanbioTM rapid antigen test kit on site, up to three times weekly for up to eight weeks per participant. We expanded the study to two more units due to low recruitment. Results: From March 30 to July 23, 2021, we tested 28 participants who underwent on average 16.5 tests participating for an average of 46 days. Of 462 rapid tests, one was positive, which was followed by a negative confirmatory polymerase chain reaction (PCR) test. The participation rate among the initially targeted population was low (16.7%). Discussion: Our study occurred during initially moderate to high but dropping community incidence rates. The positive result occurred when community transmission was low. It was likely a false positive. There were no detected or reported cases of COVID-19 among staff participants. Conclusions: Rapid antigen testing did not identify cases when used in addition to symptom- and exposure-based screening in asymptomatic staff in our small study. Recruitment was low and we suspect repeated testing by appointment was perceived as onerous.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".