Use cases for COVID-19 screening and surveillance with rapid antigen-detecting tests: a systematic review
Bibliographic record
Abstract
ABSTRACT Introduction Testing is critical to controlling the COVID-19 pandemic. Antigen-detecting rapid diagnostic tests (Ag-RDTs) that can be used at the point of care have the potential to increase access to COVID-19 testing, particularly in settings with limited laboratory capacity. This systematic review synthesized literature on specific use cases and performance of Ag-RDTs for detecting SARS-CoV-2, for the first comprehensive assessment of Ag-RDT use in real-world settings. Methods We searched three databases (PubMed, EMBASE and medRxiv) up to 12 April 2021 for publications on Ag-RDT use for large-scale screening, irrespective of symptoms, and surveillance of COVID-19, excluding studies of only presumptive COVID-19 patients. We tabulated data on the study setting, populations, type of test, diagnostic performance and operational findings. We assessed risk of bias using QUADAS-2 and an adapted tool for prevalence studies. Results From 4313 citations, 39 studies conducted in asymptomatic and symptomatic adults were included. Study sample sizes varied from 40 to >5 million. Of 39 studies, 37 (94.9%) investigated lateral flow Ag-RDTs and two (5.1%) investigated multiplex sandwich chemiluminescent enzyme immunoassay Ag-RDTs. Six categories of testing (screening/surveillance) initiatives were identified: mass screening (n=13), targeted screening (n=11), healthcare entry testing (n=6), at-home testing (n=4), surveillance (n=4) and prevalence survey (n=1). Across studies, Ag-RDT sensitivity varied from 40% to 100%. Ag-RDTs were noted as convenient, easy-to-use and low cost, with a rapid turnaround time and high user acceptability. Risk of bias was generally low or unclear across the studies. Conclusion This systematic review demonstrates the use of Ag-RDTs across a wide range of real-world settings for screening and surveillance of COVID-19 in both symptomatic and asymptomatic individuals. Ag-RDTs were overall found to be easy-to-use, low cost and rapid tools, when consideration is given to their implementation and interpretation. The review was funded by FIND, the global alliance for diagnostics. SUMMARY What is already known? Antigen-detecting rapid diagnostic tests (Ag-RDTs) have the potential to substantially improve access to timely testing for COVID-19 and are being deployed in a variety of settings around the world While studies have investigated the diagnostic accuracy of Ag-RDTs, less is known about how and in what settings Ag-RDTs are being used around the world and their performance in these different settings What are the new findings? Ag-RDTs are being used in a diverse range of real-world settings for mass screening and surveillance of COVID-19 among symptomatic and asymptomatic individuals The sensitivity of Ag-RDTs is variable - ranging from 40% to 100% - and in some cases low compared with RT-PCR, meaning that the value of testing with Ag-RDTs needs to be carefully evaluated for each use case taking into account factors such as the prevalence of COVID-19 in the population, the consequences of false positive or false negative results, and whether confirmatory testing of positive or negative Ag-RDT results with RT-PCR is required Nevertheless, Ag-RDTs are generally reported as being easy to use and low cost, with a rapid turnaround time that enables timely identification of cases and subsequent interventions to prevent onward transmission of COVID-19 What do the new findings imply? The evidence indicates that Ag-RDTs can be effectively deployed across a broad range of settings when consideration is given to how they are implemented and interpreted The development of more detailed, evidence-based testing policies for Ag-RDTs will be important to help countries implement effective testing programmes and make the best use of Ag-RDTs as part of the COVID-19 testing toolkit
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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 | 0.002 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".