Abstract
Background: SARS-CoV-2 antibody tests are used for population surveillance and might have a future role in individual risk assessment. Lateral flow immunoassays (LFIAs) can deliver results rapidly and at scale, but have widely varying accuracy.
Methods: In a laboratory setting, we performed head-to-head comparisons of four LFIAs: the Rapid Test Consortium’s AbC-19TM Rapid Test, OrientGene COVID IgG/IgM Rapid Test Cassette, SureScreen COVID-19 Rapid Test Cassette, and Biomerica COVID-19 IgG/IgM Rapid Test. We analysed blood samples from 2,847 key workers and 1,995 pre-pandemic blood donors with all four devices.
Findings: We observed a clear trade-off between sensitivity and specificity: the IgG band of the SureScreen device and the AbC-19TM device had higher specificities but OrientGene and Biomerica higher sensitivities. Based on analysis of pre-pandemic samples, SureScreen IgG band had the highest specificity (98.9%, 95% confidence interval 98.3 to 99.3%), which translated to the highest positive predictive value across any pre-test probability: for example, 95.1% (95% uncertainty interval 92.6, 96.8%) at 20% pre-test probability. All four devices showed higher sensitivity at higher antibody concentrations (“spectrum effects”), but the extent of this varied by device.
Interpretation: The estimates of sensitivity and specificity can be used to adjust for test error rates when using these devices to estimate the prevalence of antibody. If tests were used to determine whether an individual has SARS-CoV-2 antibodies, in an example scenario in which 20% of individuals have antibodies we estimate around 5% of positive results on the most specific device would be false positives.
Funding: Public Health England.
Methods: In a laboratory setting, we performed head-to-head comparisons of four LFIAs: the Rapid Test Consortium’s AbC-19TM Rapid Test, OrientGene COVID IgG/IgM Rapid Test Cassette, SureScreen COVID-19 Rapid Test Cassette, and Biomerica COVID-19 IgG/IgM Rapid Test. We analysed blood samples from 2,847 key workers and 1,995 pre-pandemic blood donors with all four devices.
Findings: We observed a clear trade-off between sensitivity and specificity: the IgG band of the SureScreen device and the AbC-19TM device had higher specificities but OrientGene and Biomerica higher sensitivities. Based on analysis of pre-pandemic samples, SureScreen IgG band had the highest specificity (98.9%, 95% confidence interval 98.3 to 99.3%), which translated to the highest positive predictive value across any pre-test probability: for example, 95.1% (95% uncertainty interval 92.6, 96.8%) at 20% pre-test probability. All four devices showed higher sensitivity at higher antibody concentrations (“spectrum effects”), but the extent of this varied by device.
Interpretation: The estimates of sensitivity and specificity can be used to adjust for test error rates when using these devices to estimate the prevalence of antibody. If tests were used to determine whether an individual has SARS-CoV-2 antibodies, in an example scenario in which 20% of individuals have antibodies we estimate around 5% of positive results on the most specific device would be false positives.
Funding: Public Health England.
| Original language | English |
|---|---|
| Article number | 103414 |
| Number of pages | 12 |
| Journal | EBioMedicine |
| Volume | 68 |
| Early online date | 4 Jun 2021 |
| DOIs | |
| Publication status | Published - Jun 2021 |
Bibliographical note
Funding Information:The study was commissioned by the UK Government's Department of Health and Social Care, and was funded and implemented by Public Health England, supported by the NIHR Clinical Research Network (CRN) Portfolio. HEJ, MH and IO acknowledge support from the NIHR Health Protection Research Unit in Behavioural Science and Evaluation at the University of Bristol. DW acknowledges support from the NIHR Health Protection Research Unit in Genomics and Data Enabling at the University of Warwick. STP is supported by an NIHR Career Development Fellowship (CDF-2016-09-018). Participants in the COMPARE study were recruited with the active collaboration of NHS Blood and Transplant (NHSBT) England ( www.nhsbt.nhs.uk ). Funding for COMPARE was provided by NHSBT and the NIHR Blood and Transplant Research Unit (BTRU) in Donor Health and Genomics (NIHR BTRU-2014-10024). DNA extraction and genotyping were co-funded by the NIHR BTRU and the NIHR BioResource ( http://bioresource.nihr.ac.uk ). The academic coordinating centre for COMPARE was supported by core funding from: NIHR BTRU, UK Medical Research Council (MR/L003120/1), British Heart Foundation (RG/13/13/30194; RG/18/13/33946) and the NIHR Cambridge Biomedical Research Centre (BRC). COMPARE was also supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Division), Public Health Agency (Northern Ireland), British Heart Foundation, and Wellcome. JD holds a British Heart Foundation professorship and an NIHR senior investigator award. SK is funded by a BHF Chair award (CH/12/2/29428). The views expressed are those of the authors and not necessarily those of the NHS, NIHR or Department of Health and Social Care.
Funding Information:
The study was commissioned by the UK Government's Department of Health and Social Care, and was funded and implemented by Public Health England, supported by the NIHR Clinical Research Network (CRN) Portfolio. HEJ, MH and IO acknowledge support from the NIHR Health Protection Research Unit in Behavioural Science and Evaluation at the University of Bristol. DW acknowledges support from the NIHR Health Protection Research Unit in Genomics and Data Enabling at the University of Warwick. STP is supported by an NIHR Career Development Fellowship (CDF-2016-09-018). Participants in the COMPARE study were recruited with the active collaboration of NHS Blood and Transplant (NHSBT) England ( www.nhsbt.nhs.uk). Funding for COMPARE was provided by NHSBT and the NIHR Blood and Transplant Research Unit (BTRU) in Donor Health and Genomics (NIHR BTRU-2014-10024). DNA extraction and genotyping were co-funded by the NIHR BTRU and the NIHR BioResource ( http://bioresource.nihr.ac.uk). The academic coordinating centre for COMPARE was supported by core funding from: NIHR BTRU, UK Medical Research Council (MR/L003120/1), British Heart Foundation (RG/13/13/30194; RG/18/13/33946) and the NIHR Cambridge Biomedical Research Centre (BRC). COMPARE was also supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Division), Public Health Agency (Northern Ireland), British Heart Foundation, and Wellcome. JD holds a British Heart Foundation professorship and an NIHR senior investigator award. SK is funded by a BHF Chair award (CH/12/2/29428). The views expressed are those of the authors and not necessarily those of the NHS, NIHR or Department of Health and Social Care. We thank the following people who supported laboratory testing, data entry and checking, and specimen management: Jake Hall, Maryam Razaei, Nipunadi Hettiarachchi, Sarah Nalukenge, Katy Moore, Maria Bolea, Palak Joshi, Matthew Hannah, Amisha Vibhakar, Siew Lin Ngui, Amy Gentle, Honor Gartland, Stephanie L Smith, Rashara Harewood, Hamish Wilson, Shabnam Jamarani, James Bull, Martha Valencia, Suzanna Barrow, Joshim Uddin, Beejal Vaghela, Shahmeen Ali. We also thank Steve Harbour and Neil Woodford, who provided staff, laboratories, and equipment; the blood donor centre staff and blood donors for participating in the COMPARE study; and Philippa Moore, Antoanela Colda and Richard Stewart for their invaluable contributions in the Milton Keynes General Hospital and Gloucestershire Hospitals study sites. SARS-CoV-2 antibody test result data on the 2,847 EDSAB-HOME study participants have been deposited on Mendeley Data (DOI: 10.17632/gnsf982vrb.1), with a data dictionary. The data set contains individual level results on the four LFIAs and two laboratory immunoassays. Study recruitment stream, previous PCR positivity and (among individuals self-reporting previous PCR positivity) whether symptomatic disease was experienced and days between symptom onset and venous blood sample being taken are also provided. COMPARE study data are provided in aggregate form in the supplementary materials (Table S18). This table provides cross tabulations of results on the four LFIA devices.
Funding Information:
The study was commissioned by the UK Government's Department of Health and Social Care (DHSC), and was funded and implemented by Public Health England, supported by the NIHR Clinical Research Network Portfolio. The DHSC had no role in the study design, data collection, analysis, interpretation of results, writing of the manuscript, or the decision to publish.
Funding Information:
JS and KP report financial activities on behalf of WHO in 2018 and 2019 in evaluation of several other rapid test kits. MH declares unrelated and unrestricted speaker fees and travel expenses in last 3 years from MSD and Gillead. JD has received grants from Merck, Novartis, Pfizer and AstraZeneca and personal fees and non-financial support from Pfizer Population Research Advisory Panel. Outside of this work, RB and EL perform meningococcal contract research on behalf of PHE for GSK, Pfizer and Sanofi Pasteur. All other authors declare no conflicts of interest.
Publisher Copyright:
© 2021 The Authors
Research Groups and Themes
- Covid19
Keywords
- COVID-19
- lateral flow devices
- serosurveillance
- seroepidemiology
- rapid testing
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