Use cases for COVID-19 screening and surveillance with rapid antigen-detecting tests: a systematic review
Notice bibliographique
Résumé
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
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,050 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,004 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».