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      Self-tests for COVID-19: What is the evidence? A living systematic review and meta-analysis (2020–2023)

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          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 and DOR 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) use of digital interventions (70.15%, 95%CI: 50.18–84.63%; n = 14). Lower sensitivity was attributed to absence of symptoms, 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%). Overall 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. These data will guide COVIDST policy. Our review demonstrates that COVIDST has paved the way for self-testing in pandemics worldwide.

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          QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies.

          In 2003, the QUADAS tool for systematic reviews of diagnostic accuracy studies was developed. Experience, anecdotal reports, and feedback suggested areas for improvement; therefore, QUADAS-2 was developed. This tool comprises 4 domains: patient selection, index test, reference standard, and flow and timing. Each domain is assessed in terms of risk of bias, and the first 3 domains are also assessed in terms of concerns regarding applicability. Signalling questions are included to help judge risk of bias. The QUADAS-2 tool is applied in 4 phases: summarize the review question, tailor the tool and produce review-specific guidance, construct a flow diagram for the primary study, and judge bias and applicability. This tool will allow for more transparent rating of bias and applicability of primary diagnostic accuracy studies.
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            Panethnic Differences in Blood Pressure in Europe: A Systematic Review and Meta-Analysis

            Background People of Sub Saharan Africa (SSA) and South Asians(SA) ethnic minorities living in Europe have higher risk of stroke than native Europeans(EU). Study objective is to provide an assessment of gender specific absolute differences in office systolic(SBP) and diastolic(DBP) blood pressure(BP) levels between SSA, SA, and EU. Methods and Findings We performed a systematic review and meta-analysis of observational studies conducted in Europe that examined BP in non-selected adult SSA, SA and EU subjects. Medline, PubMed, Embase, Web of Science, and Scopus were searched from their inception through January 31st 2015, for relevant articles. Outcome measures were mean SBP and DBP differences between minorities and EU, using a random effects model and tested for heterogeneity. Twenty-one studies involving 9,070 SSA, 18,421 SA, and 130,380 EU were included. Compared with EU, SSA had higher values of both SBP (3.38 mmHg, 95% CI 1.28 to 5.48 mmHg; and 6.00 mmHg, 95% CI 2.22 to 9.78 in men and women respectively) and DBP (3.29 mmHg, 95% CI 1.80 to 4.78; 5.35 mmHg, 95% CI 3.04 to 7.66). SA had lower SBP than EU(-4.57 mmHg, 95% CI -6.20 to -2.93; -2.97 mmHg, 95% CI -5.45 to -0.49) but similar DBP values. Meta-analysis by subgroup showed that SA originating from countries where Islam is the main religion had lower SBP and DBP values than EU. In multivariate meta-regression analyses, SBP difference between minorities and EU populations, was influenced by panethnicity and diabetes prevalence. Conclusions 1) The higher BP in SSA is maintained over decades, suggesting limited efficacy of prevention strategies in such group in Europe;2) The lower BP in Muslim populations suggests that yet untapped lifestyle and behavioral habits may reveal advantages towards the development of hypertension;3) The additive effect of diabetes, emphasizes the need of new strategies for the control of hypertension in groups at high prevalence of diabetes.
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              Rapid, point‐of‐care antigen and molecular‐based tests for diagnosis of SARS‐CoV‐2 infection

              Background Accurate rapid diagnostic tests for SARS‐CoV‐2 infection could contribute to clinical and public health strategies to manage the COVID‐19 pandemic. Point‐of‐care antigen and molecular tests to detect current infection could increase access to testing and early confirmation of cases, and expediate clinical and public health management decisions that may reduce transmission. Objectives To assess the diagnostic accuracy of point‐of‐care antigen and molecular‐based tests for diagnosis of SARS‐CoV‐2 infection. We consider accuracy separately in symptomatic and asymptomatic population groups. Search methods Electronic searches of the Cochrane COVID‐19 Study Register and the COVID‐19 Living Evidence Database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) were undertaken on 30 Sept 2020. We checked repositories of COVID‐19 publications and included independent evaluations from national reference laboratories, the Foundation for Innovative New Diagnostics and the Diagnostics Global Health website to 16 Nov 2020. We did not apply language restrictions. Selection criteria We included studies of people with either suspected SARS‐CoV‐2 infection, known SARS‐CoV‐2 infection or known absence of infection, or those who were being screened for infection. We included test accuracy studies of any design that evaluated commercially produced, rapid antigen or molecular tests suitable for a point‐of‐care setting (minimal equipment, sample preparation, and biosafety requirements, with results within two hours of sample collection). We included all reference standards that define the presence or absence of SARS‐CoV‐2 (including reverse transcription polymerase chain reaction (RT‐PCR) tests and established diagnostic criteria). Data collection and analysis Studies were screened independently in duplicate with disagreements resolved by discussion with a third author. Study characteristics were extracted by one author and checked by a second; extraction of study results and assessments of risk of bias and applicability (made using the QUADAS‐2 tool) were undertaken independently in duplicate. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test and pooled data using the bivariate model separately for antigen and molecular‐based tests. We tabulated results by test manufacturer and compliance with manufacturer instructions for use and according to symptom status. Main results Seventy‐eight study cohorts were included (described in 64 study reports, including 20 pre‐prints), reporting results for 24,087 samples (7,415 with confirmed SARS‐CoV‐2). Studies were mainly from Europe (n = 39) or North America (n = 20), and evaluated 16 antigen and five molecular assays. We considered risk of bias to be high in 29 (37%) studies because of participant selection; in 66 (85%) because of weaknesses in the reference standard for absence of infection; and in 29 (37%) for participant flow and timing. Studies of antigen tests were of a higher methodological quality compared to studies of molecular tests, particularly regarding the risk of bias for participant selection and the index test. Characteristics of participants in 35 (45%) studies differed from those in whom the test was intended to be used and the delivery of the index test in 39 (50%) studies differed from the way in which the test was intended to be used. Nearly all studies (97%) defined the presence or absence of SARS‐CoV‐2 based on a single RT‐PCR result, and none included participants meeting case definitions for probable COVID‐19. Antigen tests Forty‐eight studies reported 58 evaluations of antigen tests. Estimates of sensitivity varied considerably between studies. There were differences between symptomatic (72.0%, 95% CI 63.7% to 79.0%; 37 evaluations; 15530 samples, 4410 cases) and asymptomatic participants (58.1%, 95% CI 40.2% to 74.1%; 12 evaluations; 1581 samples, 295 cases). Average sensitivity was higher in the first week after symptom onset (78.3%, 95% CI 71.1% to 84.1%; 26 evaluations; 5769 samples, 2320 cases) than in the second week of symptoms (51.0%, 95% CI 40.8% to 61.0%; 22 evaluations; 935 samples, 692 cases). Sensitivity was high in those with cycle threshold (Ct) values on PCR ≤25 (94.5%, 95% CI 91.0% to 96.7%; 36 evaluations; 2613 cases) compared to those with Ct values >25 (40.7%, 95% CI 31.8% to 50.3%; 36 evaluations; 2632 cases). Sensitivity varied between brands. Using data from instructions for use (IFU) compliant evaluations in symptomatic participants, summary sensitivities ranged from 34.1% (95% CI 29.7% to 38.8%; Coris Bioconcept) to 88.1% (95% CI 84.2% to 91.1%; SD Biosensor STANDARD Q). Average specificities were high in symptomatic and asymptomatic participants, and for most brands (overall summary specificity 99.6%, 95% CI 99.0% to 99.8%). At 5% prevalence using data for the most sensitive assays in symptomatic people (SD Biosensor STANDARD Q and Abbott Panbio), positive predictive values (PPVs) of 84% to 90% mean that between 1 in 10 and 1 in 6 positive results will be a false positive, and between 1 in 4 and 1 in 8 cases will be missed. At 0.5% prevalence applying the same tests in asymptomatic people would result in PPVs of 11% to 28% meaning that between 7 in 10 and 9 in 10 positive results will be false positives, and between 1 in 2 and 1 in 3 cases will be missed. No studies assessed the accuracy of repeated lateral flow testing or self‐testing. Rapid molecular assays Thirty studies reported 33 evaluations of five different rapid molecular tests. Sensitivities varied according to test brand. Most of the data relate to the ID NOW and Xpert Xpress assays. Using data from evaluations following the manufacturer’s instructions for use, the average sensitivity of ID NOW was 73.0% (95% CI 66.8% to 78.4%) and average specificity 99.7% (95% CI 98.7% to 99.9%; 4 evaluations; 812 samples, 222 cases). For Xpert Xpress, the average sensitivity was 100% (95% CI 88.1% to 100%) and average specificity 97.2% (95% CI 89.4% to 99.3%; 2 evaluations; 100 samples, 29 cases). Insufficient data were available to investigate the effect of symptom status or time after symptom onset. Authors' conclusions Antigen tests vary in sensitivity. In people with signs and symptoms of COVID‐19, sensitivities are highest in the first week of illness when viral loads are higher. The assays shown to meet appropriate criteria, such as WHO's priority target product profiles for COVID‐19 diagnostics (‘acceptable’ sensitivity ≥ 80% and specificity ≥ 97%), can be considered as a replacement for laboratory‐based RT‐PCR when immediate decisions about patient care must be made, or where RT‐PCR cannot be delivered in a timely manner. Positive predictive values suggest that confirmatory testing of those with positive results may be considered in low prevalence settings. Due to the variable sensitivity of antigen tests, people who test negative may still be infected. Evidence for testing in asymptomatic cohorts was limited. Test accuracy studies cannot adequately assess the ability of antigen tests to differentiate those who are infectious and require isolation from those who pose no risk, as there is no reference standard for infectiousness. A small number of molecular tests showed high accuracy and may be suitable alternatives to RT‐PCR. However, further evaluations of the tests in settings as they are intended to be used are required to fully establish performance in practice. Several important studies in asymptomatic individuals have been reported since the close of our search and will be incorporated at the next update of this review. Comparative studies of antigen tests in their intended use settings and according to test operator (including self‐testing) are required. How accurate are rapid tests for diagnosing COVID‐19? What are rapid point‐of‐care tests for COVID‐19? Rapid point‐of‐care tests aim to confirm or rule out COVID‐19 infection in people with or without COVID‐19 symptoms. They: ‐ are portable, so they can be used wherever the patient is (at the point of care); ‐ are easy to perform, with a minimum amount of extra equipment or complicated preparation steps; ‐ are less expensive than standard laboratory tests; ‐ do not require a specialist operator or setting; and ‐ provide results ‘while you wait’. We were interested in two types of commercially available, rapid point‐of‐care tests: antigen and molecular tests. Antigen tests identify proteins on the virus; they come in disposable plastic cassettes, similar to pregnancy tests. Rapid molecular tests detect the virus’s genetic material in a similar way to laboratory methods, but using smaller devices that are easy to transport or to set up outside of a specialist laboratory. Both test nose or throat samples. Why is this question important? People with suspected COVID‐19 need to know quickly whether they are infected, so that they can self‐isolate, receive treatment, and inform close contacts. Currently, COVID‐19 infection is confirmed by a laboratory test called RT‐PCR, which uses specialist equipment and often takes at least 24 hours to produce a result. Rapid point‐of‐care tests could open access to testing for many more people, with and without symptoms, potentially in locations other than healthcare settings. If they are accurate, faster diagnosis could allow people to take appropriate action more quickly, with the potential to reduce the spread of COVID‐19. What did we want to find out? We wanted to know whether commercially available, rapid point‐of‐care antigen and molecular tests are accurate enough to diagnose COVID‐19 infection reliably, and to find out if accuracy differs in people with and without symptoms. What did we do? We looked for studies that measured the accuracy of any commercially produced, rapid antigen or molecular point‐of‐care test, in people tested for COVID‐19 using RT‐PCR. People could be tested in hospital or the community. Studies could test people with or without symptoms. Tests had to use minimal equipment, be performed safely without risking infection from the sample, and have results available within two hours of the sample being collected. What we found We included 64 studies in the review. They investigated a total of 24,087 nose or throat samples; COVID‐19 was confirmed in 7415 of these samples. Studies investigated 16 different antigen tests and five different molecular tests. They took place mainly in Europe and North America. Main results Antigen tests In people with confirmed COVID‐19, antigen tests correctly identified COVID‐19 infection in an average of 72% of people with symptoms, compared to 58% of people without symptoms. Tests were most accurate when used in the first week after symptoms first developed (an average of 78% of confirmed cases had positive antigen tests). This is likely to be because people have the most virus in their system in the first days after they are infected. In people who did not have COVID‐19, antigen tests correctly ruled out infection in 99.5% of people with symptoms and 98.9% of people without symptoms. Different brands of tests varied in accuracy. Pooled results for one test (SD Biosensor STANDARD Q) met World Health Organization (WHO) standards as ‘acceptable’ for confirming and ruling out COVID‐19 in people with signs and symptoms of COVID‐19. Two more tests met the WHO acceptable standards (Abbott Panbio and BIONOTE NowCheck) in at least one study. Using summary results for SD Biosensor STANDARD Q, if 1000 people with symptoms had the antigen test, and 50 (5%) of them really had COVID‐19: ‐ 53 people would test positive for COVID‐19. Of these, 9 people (17%) would not have COVID‐19 (false positive result). ‐ 947 people would test negative for COVID‐19. Of these, 6 people (0.6%) would actually have COVID‐19 (false negative result). In people with no symptoms of COVID‐19 the number of confirmed cases is expected to be much lower than in people with symptoms. Using summary results for SD Biosensor STANDARD Q in a bigger population of 10,000 people with no symptoms, where 50 (0.5%) of them really had COVID‐19: ‐ 125 people would test positive for COVID‐19. Of these, 90 people (72%) would not have COVID‐19 (false positive result). ‐ 9,875 people would test negative for COVID‐19. Of these, 15 people (0.2%) would actually have COVID‐19 (false negative result). Molecular tests Although overall results for diagnosing and ruling out COVID‐19 were good (95.1% of infections correctly diagnosed and 99% correctly ruled out), 69% of the studies used the tests in laboratories instead of at the point‐of‐care and few studies followed test manufacturer instructions. Most of the data relate to the ID NOW and Xpert Xpress tests. We noted a large difference in COVID‐19 detection between the two tests, but we cannot be certain about whether results will remain the same in a real world setting. We could not investigate differences in people with or without symptoms, nor time from when symptoms first showed because the studies did not provide enough information about their participants. How reliable were the results of the studies? In general, studies that assessed antigen tests used more rigorous methods than those that assessed molecular tests, particularly when selecting participants and performing the tests. Sometimes studies did not perform the test on the people for whom it was intended and did not follow the manufacturers’ instructions for using the test. Sometimes the tests were not carried out at the point‐of‐care. Nearly all the studies (97%) relied on a single negative RT‐PCR result as evidence of no COVID‐19 infection. Results from different test brands varied, and few studies directly compared one test brand with another. Finally, not all studies gave enough information about their participants for us to judge how long they had had symptoms, or even whether or not they had symptoms. What does this mean? Some antigen tests are accurate enough to replace RT‐PCR when used in people with symptoms. This would be most useful when quick decisions are needed about patient care, or if RT‐PCR is not available. Antigen tests may be most useful to identify outbreaks, or to select people with symptoms for further testing with PCR, allowing self‐isolation or contact tracing and reducing the burden on laboratory services. People who receive a negative antigen test result may still be infected. Several point‐of‐care molecular tests show very high accuracy and potential for use, but more evidence of their performance when evaluated in real life settings is required. We need more evidence on rapid testing in people without symptoms, on the accuracy of repeated testing, testing in non‐healthcare settings such as schools (including self‐testing), and direct comparisons of test brands, with testers following manufacturers’ instructions. How up‐to‐date is this review? This review updates our previous review and includes evidence published up to 30 September 2020.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: MethodologyRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLOS Glob Public Health
                PLOS Glob Public Health
                plos
                PLOS Global Public Health
                Public Library of Science (San Francisco, CA USA )
                2767-3375
                7 February 2024
                2024
                : 4
                : 2
                : e0002336
                Affiliations
                [1 ] Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
                [2 ] Infectious Diseases and Immunity in Global Health, Research Institute of McGill University Health Centre, Montreal, Quebec, Canada
                [3 ] Faculty of Medicine, McGill University, Montreal, Quebec, Canada
                [4 ] Centre for Lung Infection and Immunity, Division of Pulmonology, UCT Lung Institute and Department of Medicine, University of Cape Town, Cape Town, Western Cape, South Africa
                [5 ] Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada
                University of Embu, KENYA
                Author notes

                I have read the journal’s policy and the authors of this manuscript have the following competing interests: NPP reports an open access application for COVID self-testing: “COVIDSmart CARE!”, McGill University Copyright 2022-002. This digital innovation was supported by the CIHR grant no FRN 174921.

                Author information
                https://orcid.org/0000-0001-8575-436X
                https://orcid.org/0000-0002-4672-0500
                Article
                PGPH-D-23-01541
                10.1371/journal.pgph.0002336
                10849237
                38324519
                c3884b4d-3743-439e-aa64-b39a3b13086b
                © 2024 Anand et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 5 August 2023
                : 18 January 2024
                Page count
                Figures: 3, Tables: 1, Pages: 20
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;
                Award ID: 174921
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000156, Fonds de Recherche du Québec - Santé;
                Award ID: 324154
                Award Recipient :
                NPP, KD received funding from Canadian Institutes of Health Research (CIHR) (Grant Number: 174921) and Fonds de recherche du Québec – Santé (Merité award: 313488). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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