Self-tests for COVID-19: what is the evidence? A living systematic review and meta-analysis (2020-2023)
Bibliographic record
Abstract
Abstract COVID-19 self-testing strategy (COVIDST) can rapidly identify symptomatic and asymptomatic SARS-CoV-2-infected individuals and their contacts, potentially reducing transmission. In this living systematic review, we evaluated the evidence for real-world COVIDST performance. Two independent reviewers searched six databases (PubMed, Embase, Web of Science, World Health Organization database, Cochrane COVID-19 registry, Europe PMC) for the period April 1 st , 2020, to January 18 th , 2023. Data on studies evaluating COVIDST against laboratory-based conventional testing and reported on diagnostic accuracy, feasibility, acceptability, impact, and qualitative outcomes were abstracted. Bivariate random effects meta-analyses of COVIDST accuracy were performed (n=14). Subgroup analyses (by sampling site, symptomatic/asymptomatic infection, supervised/unsupervised strategy, with/without digital supports) were conducted. Data from 70 included studies, conducted across 25 countries with a median sample size of 817 (range: 28-784,707) were pooled. Specificity was high overall, irrespective of subgroups (98.37-99.71%). Highest sensitivities were reported for: a) symptomatic individuals (73.91%, 95%CI: 68.41-78.75%; n=9), b) mid-turbinate nasal samples (77.79%, 95%CI: 56.03-90.59%; n=14), c) supervised strategy (86.67%, 95%CI: 59.64-96.62%; n=13), and d) presence of digital interventions (70.15%, 95%CI: 50.18-84.63%; n=14). Sensitivity was lower in asymptomatic populations (40.18%, 95% CI: 21.52-62.20%; n=4), due to errors in test conduct and absence of supervision or a digital support. We found no difference in COVIDST sensitivity between delta and omicron pre-dominant period. Digital supports increased confidence in COVIDST reporting and interpretation (n=16). Overall acceptability was 91.0-98.7% (n=2) with lower acceptability reported for daily self-testing (39.5-51.1%). Feasibility was 69.0-100.0% (n=5) with lower feasibility (35.9-64.6%) for serial self-testing. COVIDST decreased closures in school, workplace, and social events (n=4). COVIDST is an effective rapid screening strategy for home-, workplace- or school-based screening, for symptomatic persons, and for preventing transmission during outbreaks. This data is useful for updating COVIDST policy. Our review demonstrates that COVIDST has paved the way for the introduction of self-tests, worldwide.
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How this classification was reachedexpand
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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".