Use cases for COVID-19 screening and surveillance with rapid antigen-detecting tests: a systematic review
Authors: Anand Apoorva , Bigio Jacob , MacLean Emily , Underwood Talya , Pai Nitika Pant , Carmona Sergio , Schumacher Samuel G. , Toporowski Amy 
Published: November 2021

ABSTRACTIntroductionTesting 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.MethodsWe 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.ResultsFrom 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.ConclusionThis 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.SUMMARYWhat 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 worldWhile 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 settingsWhat 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 individualsThe 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 requiredNevertheless, 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-19What 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 interpretedThe 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