Four COVID-19 screening strategies for early case identification within the homeless shelter population: a cluster randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: To compare the effectiveness of four surveillance strategies for detecting SARS-CoV-2 within the homeless shelter population in Hamilton, ON and assess participant adherence over time for each surveillance method. METHODS: This was an open-label, cluster-randomized controlled trial conducted in eleven homeless shelters in Hamilton, Ontario, from April 2020 to January 2021. All participants who consented to the study and participated in the surveillance were eligible for testing by self-swabbing. SARS-CoV-2 detection rate as the primary outcome, number of outbreaks, adherence, and overall acceptability were assessed. All participants, which included staff and residents, underwent daily symptom surveillance conducted by shelter staff and shelters were allocated to one of three asymptomatic surveillance arms (once weekly, self-collected oral swabs (OS); once-weekly self-collected oral-nasal swab (ONS); or once-weekly nurse collected nasopharyngeal swab (NPS) or a symptomatic only SARS-CoV-2 testing arm. RESULTS: A total of 9747 SARS-CoV-2 tests were performed on 1570 participants. There were 4527 participants allocated to oral swab collection and 4935 participants allocated to oral-nasal swab collection. For nasopharyngeal swab collection, 285 participants were assigned before this arm was discontinued. The OS group identified 5 new cases (1.1 per 1000; 95% CI 0.4-2.3), while the ONS group identified 15 new cases (3.0 per 1000; 95% CI 1.9-4.7), resulting in a Risk Ratio (RR) of 2.76 (95% CI 1.00-7.58; p = 0.040). However, the mixed-effect model did not show a significantly higher positivity rate in the ONS compared to OS (OR 1.64; 95% CI 0.76-9.14; p = 0.129). Both ONS and OS were preferred over NPS, which did not detect any cases due to low adherence. Three outbreaks were identified during the study period within the shelters, two of the outbreaks had 2 positive cases each and the third outbreak had 3 positive cases. CONCLUSIONS: The two self-collection strategies were superior and showed the best adherence, with the ONS strategy shown to be superior or non-inferior in all measures. We are now studying the operationalization of a large-scale self-collected ONS surveillance strategy in a prospective cohort study of multiple homeless shelters. Funding was provided by the Hamilton Academic Hospital Organization (HAHSO) and Research St. Joseph's - Hamilton. TRIAL REGISTRATION: The trial was retrospectively registered with ClinicalTrials.gov on June 18, 2020, with the identifier NCT04438070.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".