The Cochrane database of systematic reviewsOct 14, 2024

Lab tests other than RT-PCR for diagnosing COVID-19 infection

Updated Apr 6, 2026

Abstract

The analysis included data from 94 cohorts with 74,753 samples and 7,517 confirmed SARS-CoV-2 cases.

RT-PCR assays designed to omit/adapt RNA extraction/purification showed an average sensitivity of 95.1% and specificity of 99.7%.
TMA assays exhibited an average sensitivity of 97.6% and specificity of 99.4%.
RT-LAMP assays demonstrated an average sensitivity of 88.4% and specificity of 99.7%.
Only RT-PCR and TMA assays met the WHO-acceptable sensitivity and specificity requirements for SARS-CoV-2 nucleic acid tests.
At 5% prevalence, the positive predictive value for RT-PCR assays was 94%, while TMA assays had a positive predictive value of 89%.
Several alternative assay technologies remain inadequately evaluated, leading to uncertainty about their performance.

Simplified

BACKGROUND: Diagnosing people with a SARS-CoV-2 infection played a critical role in managing the COVID-19 pandemic and remains a priority for the transition to long-term management of COVID-19. Initial shortages of extraction and reverse transcription polymerase chain reaction (RT-PCR) reagents impaired the desired upscaling of testing in many countries, which led to the search for alternatives to RNA extraction/purification and RT-PCR testing. Reference standard methods for diagnosing the presence of SARS-CoV-2 infection rely primarily on real-time reverse transcription-polymerase chain reaction (RT-PCR). Alternatives to RT-PCR could, if sufficiently accurate, have a positive impact by expanding the range of diagnostic tools available for the timely identification of people infected by SARS-CoV-2, access to testing and the use of resources.

OBJECTIVES: To assess the diagnostic accuracy of alternative (to RT-PCR assays) laboratory-based molecular tests for diagnosing SARS-CoV-2 infection.

SEARCH METHODS: We searched the COVID-19 Open Access Project living evidence database from the University of Bern until 30 September 2020 and the WHO COVID-19 Research Database until 31 October 2022. We did not apply language restrictions.

SELECTION CRITERIA: We included studies of people with suspected or known SARS-CoV-2 infection, or where tests were used to screen for infection, and studies evaluating commercially developed laboratory-based molecular tests for the diagnosis of SARS-CoV-2 infection considered as alternatives to RT-PCR testing. We also included all reference standards to define the presence or absence of SARS-CoV-2, including RT-PCR tests and established clinical diagnostic criteria.

DATA COLLECTION AND ANALYSIS: Two authors independently screened studies and resolved disagreements by discussing them with a third author. Two authors independently extracted data and assessed the risk of bias and applicability of the studies using the QUADAS-2 tool. We presented sensitivity and specificity, with 95% confidence intervals (CIs), for each test using paired forest plots and summarised results using average sensitivity and specificity using a bivariate random-effects meta-analysis. We illustrated the findings per index test category and assay brand compared to the WHO's acceptable sensitivity and specificity threshold for diagnosing SARS-CoV-2 infection using nucleic acid tests.

MAIN RESULTS: We included data from 64 studies reporting 94 cohorts of participants and 105 index test evaluations, with 74,753 samples and 7517 confirmed SARS-CoV-2 cases. We did not identify any published or preprint reports of accuracy for a considerable number of commercially produced NAAT assays. Most cohorts were judged at unclear or high risk of bias in more than three QUADAS-2 domains. Around half of the cohorts were considered at high risk of selection bias because of recruitment based on COVID status. Three quarters of 94 cohorts were at high risk of bias in the reference standard domain because of reliance on a single RT-PCR result to determine the absence of SARS-CoV-2 infection or were at unclear risk of bias due to a lack of clarity about the time interval between the index test assessment and the reference standard, the number of missing results, or the absence of a participant flow diagram. For index tests categories with four or more evaluations and when summary estimations were possible, we found that: a) For RT-PCR assays designed to omit/adapt RNA extraction/purification, the average sensitivity was 95.1% (95% CI 91.1% to 97.3%), and the average specificity was 99.7% (95% CI 98.5% to 99.9%; based on 27 evaluations, 2834 samples and 1178 SARS-CoV-2 cases); b) For RT-LAMP assays, the average sensitivity was 88.4% (95% CI 83.1% to 92.2%), and the average specificity was 99.7% (95% CI 98.7% to 99.9%; 24 evaluations, 29,496 samples and 2255 SARS-CoV-2 cases); c) for TMA assays, the average sensitivity was 97.6% (95% CI 95.2% to 98.8%), and the average specificity was 99.4% (95% CI 94.9% to 99.9%; 14 evaluations, 2196 samples and 942 SARS-CoV-2 cases); d) for digital PCR assays, the average sensitivity was 98.5% (95% CI 95.2% to 99.5%), and the average specificity was 91.4% (95% CI 60.4% to 98.7%; five evaluations, 703 samples and 354 SARS-CoV-2 cases); e) for RT-LAMP assays omitting/adapting RNA extraction, the average sensitivity was 73.1% (95% CI 58.4% to 84%), and the average specificity was 100% (95% CI 98% to 100%; 24 evaluations, 14,342 samples and 1502 SARS-CoV-2 cases). Only two index test categories fulfil the WHO-acceptable sensitivity and specificity requirements for SARS-CoV-2 nucleic acid tests: RT-PCR assays designed to omit/adapt RNA extraction/purification and TMA assays. In addition, WHO-acceptable performance criteria were met for two assays out of 35 when tests were used according to manufacturer instructions. At 5% prevalence using a cohort of 1000 people suspected of SARS-CoV-2 infection, the positive predictive value of RT-PCR assays omitting/adapting RNA extraction/purification will be 94%, with three in 51 positive results being false positives, and around two missed cases. For TMA assays, the positive predictive value of RT-PCR assays will be 89%, with 6 in 55 positive results being false positives, and around one missed case.

AUTHORS' CONCLUSIONS: Alternative laboratory-based molecular tests aim to enhance testing capacity in different ways, such as reducing the time, steps and resources needed to obtain valid results. Several index test technologies with these potential advantages have not been evaluated or have been assessed by only a few studies of limited methodological quality, so the performance of these kits was undetermined. Only two index test categories with enough evaluations for meta-analysis fulfil the WHO set of acceptable accuracy standards for SARS-CoV-2 nucleic acid tests: RT-PCR assays designed to omit/adapt RNA extraction/purification and TMA assays. These assays might prove to be suitable alternatives to RT-PCR for identifying people infected by SARS-CoV-2, especially when the alternative would be not having access to testing. However, these findings need to be interpreted and used with caution because of several limitations in the evidence, including reliance on retrospective samples without information about the symptom status of participants and the timing of assessment. No extrapolation of found accuracy data for these two alternatives to any test brands using the same techniques can be made as, for both groups, one test brand with high accuracy was overrepresented with 21/26 and 12/14 included studies, respectively. Although we used a comprehensive search and had broad eligibility criteria to include a wide range of tests that could be alternatives to RT-PCR methods, further research is needed to assess the performance of alternative COVID-19 tests and their role in pandemic management.

Funding

Competing interests

Ingrid Arevalo‐Rodriguez: IAR has been an employee of the Cochrane Central Executive Team (Cochrane Response/Evidence, Production & Methods Directorate) since 2021. Miriam Mateos: none known. Jacqueline Dinnes: none known. Clare Davenport: none known. Agustin Ciapponi: none known. Diana Buitrago‐Garcia: none known. Tayeb Bennouna Dalero: none known. Marta Roque‐Figuls: none known. Ann Van den Bruel: none known. Karin Jasmijn von Eije: KVE worked as a staff member till mid‐January 2021 for WHO; in that capacity, she has been involved in guidance on SARS‐CoV‐2 diagnostics. After that, she worked as a clinical virologist at the UMCG in Groningen and, in that capacity, was not directly involved in activities of WHO regarding guidance on molecular diagnostics for SARS‐CoV‐2; her contracted work did include work focused on the WHO SARS‐CoV‐2 laboratory network until August 2023. Since September 2023, she has worked at the Erasmus MC, University Medical Center, as a clinical virologist and has continued to perform contracted work, but not on WHO guidance on clinical molecular diagnostics for SARS‐CoV‐2 or the WHO SARS‐CoV‐2 laboratory network. Devy Emperador: DE is employed by FIND with funding from DFID and KFW. FIND is a global non‐for‐profit product development partnership and WHO Diagnostic Collaboration Centre. It is FIND's role to accelerate access to high‐quality diagnostic tools for low‐resource settings, and this is achieved by supporting both R&D and access activities for a wide range of diseases, including COVID‐19. FIND has several clinical research projects to evaluate multiple new diagnostic tests against published Target Product Profiles that have been defined through consensus processes. These studies are for diagnostic products developed by private sector companies who provide access to know‐how, equipment/reagents, and contribute through unrestricted donations as per FIND policy and external SAC review. Lotty Hooft: none known. Mariska MG Leeflang: none known. René Spijker: the Dutch Cochrane Centre (DCC) has received grants for performing commissioned systematic reviews. The commissioner did not have any influence on the results of this work. Yemisi Takwoingi: none known. Jonathan J Deeks: JD has published or been quoted in opinion pieces in scientific publications, and in the mainstream and social media related to diagnostic testing. JD is a member of the Royal Statistical Society (RSS) COVID‐19 task force steering group and co‐chair of the RSS Diagnostic Test Advisory Group. He is a consultant adviser to the WHO Essential Diagnostic List. JD receives payment from the BMJ as their Chief Statistical advisor.

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Abstract

Funding

Competing interests

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