Antibody testing for COVID-19: A report from the National COVID Scientific Advisory Panel

Adams, Emily; Ainsworth, Mark; Anand, Rekha; Andersson, Monique; Auckland, Kathryn; Baillie, J Kenneth; Barnes, Eleanor; Beer, Sally; Bell, John I.; Berry, T; Bibi, Sagida; Carroll, Miles W.; Chinnakannan, Senthil; Clutterbuck, Elizabeth A.; Cornall, Richard J.; Crook, Derrick W.; Silva, Thushan I. de; Dejnirattisai, Wanwisa; Dingle, Kate E.; Dold, Christina; Espinosa, Alexis; Eyre, David W; Farmer, H.; Mendoza, Maria Fernandez; Georgiou, Dominique; Hoosdally, Sarah; Hunter, A; Jefferey, K; Kelly, Dominic F.; Klenerman, Paul; Knight, Julian C.; Knowles, C; Kwok, Andrew; Leuschner, U; Levin, Robert H.; Liu, C; López-Camacho, César; Martinez, Jose; Matthews, Philippa C.; McGivern, Hannah; Mentzer, Alexander J.; Milton, J; Mongkolsapaya, Juthathip; Moore, Shona C.; Oliveira, Marta; Pereira, Fiona; Perez, Elena; Peto, Timothy E. A.; Ploeg, Rutger J.; Pollard, Andrew J.; Prince, Tessa; Roberts, David; Rudkin, Justine; Sánchez, Verónica; Screaton, Gavin; Semple, Malcolm G; Slon-Campos, J; Skelly, Donal; Smith, E. B.; Sobrinodiaz, Alberto; Staves, Julie; Stuart, David I.; Supasa, Piyasa; Surik, Tomas; Thraves, Hannah; Tsang, Pat; Turtle, Lance; Walker, A Sarah; Wang, Beibei; Washington, Charlotte; Watkins, Nicholas A.; Whitehouse, James

doi:10.12688/wellcomeopenres.15927.1

Cited by 210 publications

(208 citation statements)

References 24 publications

Supporting

Mentioning

194

Contrasting

Unclassified

Order By: Relevance

“…At the early stages of SARS-CoV-2 infection IgG/M assays are likely to have false negative results and miss cases due to the fact that a detectable antibody response to SARS-CoV-2 infection can take more than ten days after the onset of symptoms 28 . The subsequent increase is in line with published findings 30 . Further, an increase in IgG and/or IgM during the first three weeks is also recorded 19,[31][32][33] .…”

Section: Discussionsupporting

confidence: 93%

Diagnostic accuracy estimates for COVID-19 RT-PCR and Lateral flow immunoassay tests with Bayesian latent class models

Kostoulas

Hartnack

2020

Preprint

View full text Add to dashboard Cite

The objective of this work was to estimate the diagnostic accuracy of RT-PCR and Lateral flow immunoassay tests (LFIA) for COVID-19, depending on the time post symptom onset. Based on the cross-classified results of RT-PCR and LFIA, we used Bayesian latent class models (BLCMs), which do not require a gold standard for the evaluation of diagnostics. Data were extracted from studies that evaluated LFIA (IgG and/or IgM) assays using RT-PCR as the reference method. The cross-classified results of LFIA and RT-PCR were analysed separately for the first, second and third week post symptom onset. The SeRT-PCR was 0.695 (95% probability intervals: 0.563; 0.837) for the first week and remained similar for the second and the third week. The SeIgG/M was 0.318 (0.229; 0.416) for the first week and increased steadily. It was 0.755 (0.673; 0.829) and 0.927 (0.881; 0.965) for the second and third week, respectively. Both tests had a high to absolute Sp, with point median estimates for SpRT-PCR being consistently higher. SpRT-PCR was 0.990 (0.980; 0.998) for the first week. The corresponding value for SpIgG/M was 0.962 (0.905; 0.998). Further, Sp estimates for each test did not differ between weeks. BLCMs provide a valid and efficient alternative for evaluating the rapidly evolving diagnostics for COVID-19, under various clinical settings and for different risk profiles.

show abstract

Section: Discussionsupporting

confidence: 93%

Diagnostic accuracy estimates for COVID-19 RT-PCR and Lateral flow immunoassay tests with Bayesian latent class models

Kostoulas

Hartnack

2020

Preprint

View full text Add to dashboard Cite

show abstract

“… 2 Immunoassays detect either specific types of antibody (eg, IgM or IgG) or total antibody. SARS-CoV-2 antibodies typically start to appear at least 5–7 days post infection 3 and are therefore an unreliable marker for early acute infection. The degree and duration of immunity that antibodies confer are unclear.…”

Section: Introductionmentioning

confidence: 99%

Performance characteristics of five immunoassays for SARS-CoV-2: a head-to-head benchmark comparison

Ainsworth¹,

Andersson²,

Auckland³

et al. 2020

The Lancet Infectious Diseases

Self Cite

356

291

View full text Add to dashboard Cite

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic in 2020. Testing is crucial for mitigating public health and economic effects. Serology is considered key to population-level surveillance and potentially individual-level risk assessment. However, immunoassay performance has not been compared on large, identical sample sets. We aimed to investigate the performance of four high-throughput commercial SARS-CoV-2 antibody immunoassays and a novel 384-well ELISA. Methods We did a head-to-head assessment of SARS-CoV-2 IgG assay (Abbott, Chicago, IL, USA), LIAISON SARS-CoV-2 S1/S2 IgG assay (DiaSorin, Saluggia, Italy), Elecsys Anti-SARS-CoV-2 assay (Roche, Basel, Switzerland), SARS-CoV-2 Total assay (Siemens, Munich, Germany), and a novel 384-well ELISA (the Oxford immunoassay). We derived sensitivity and specificity from 976 pre-pandemic blood samples (collected between Sept 4, 2014, and Oct 4, 2016) and 536 blood samples from patients with laboratory-confirmed SARS-CoV-2 infection, collected at least 20 days post symptom onset (collected between Feb 1, 2020, and May 31, 2020). Receiver operating characteristic (ROC) curves were used to assess assay thresholds. Findings At the manufacturers' thresholds, for the Abbott assay sensitivity was 92·7% (95% CI 90·2–94·8) and specificity was 99·9% (99·4–100%); for the DiaSorin assay sensitivity was 95·0% (92·8–96·7) and specificity was 98·7% (97·7–99·3); for the Oxford immunoassay sensitivity was 99·1% (97·8–99·7) and specificity was 99·0% (98·1–99·5); for the Roche assay sensitivity was 97·2% (95·4–98·4) and specificity was 99·8% (99·3–100); and for the Siemens assay sensitivity was 98·1% (96·6–99·1) and specificity was 99·9% (99·4–100%). All assays achieved a sensitivity of at least 98% with thresholds optimised to achieve a specificity of at least 98% on samples taken 30 days or more post symptom onset. Interpretation Four commercial, widely available assays and a scalable 384-well ELISA can be used for SARS-CoV-2 serological testing to achieve sensitivity and specificity of at least 98%. The Siemens assay and Oxford immunoassay achieved these metrics without further optimisation. This benchmark study in immunoassay assessment should enable refinements of testing strategies and the best use of serological testing resource to benefit individuals and population health. Funding Public Health England and UK National Institute for Health Research.

show abstract

“…We included articles available up to May 1 2020 that contained data that could be used for the analyses in this study. This resulted in a final subset containing 19 peer-reviewed articles and two preprints ( Yongchen et al, 2020 ; Du et al, 2020 ; To et al, 2020 ; Wölfel et al, 2020 ; Okba et al, 2020 ; Zhao et al, 2020 ; Haveri et al, 2020 ; Xiao et al, 2020 ; Jiang et al, 2020 ; Lee et al, 2020 ; Liu et al, 2020a ; Long et al, 2020 ; Lou et al, 2020 ; Thevarajan et al, 2020 ; Xiang et al, 2020 ; Zhang et al, 2020a ; Zhou et al, 2020 ; Young et al, 2020 ; Zhang et al, 2020b ; Liu et al, 2020b ; Zhang et al, 2020c ; Adams et al, 2020 ; Zou et al, 2020 ). Note that initial article selection sample sizes are approximate due to the way in which Google Scholar reports the number of results.…”

Section: Methodsmentioning

confidence: 99%

Quantifying antibody kinetics and RNA detection during early-phase SARS-CoV-2 infection by time since symptom onset

Borremans

Gamble

Prager

et al. 2020

eLife

View full text Add to dashboard Cite

Understanding and mitigating SARS-CoV-2 transmission hinges on antibody and viral RNA data that inform exposure and shedding, but extensive variation in assays, study group demographics and laboratory protocols across published studies confounds inference of true biological patterns. Our meta-analysis leverages 3,214 datapoints from 516 individuals in 21 studies to reveal that seroconversion of both IgG and IgM occurs around 12 days post symptom onset (range 1-40), with extensive individual variation that is not significantly associated with disease severity. IgG and IgM detection probabilities increase from roughly 10% at symptom onset to 98-100% by day 22, after which IgM wanes while IgG remains reliably detectable. RNA detection probability decreases from roughly 90% to zero by day 30, and is highest in faeces and lower respiratory tract samples. Our findings provide a coherent evidence base for interpreting clinical diagnostics, and for the mathematical models and serological surveys that underpin public health policies.

show abstract

Antibody testing for COVID-19: A report from the National COVID Scientific Advisory Panel

Cited by 210 publications

References 24 publications

Diagnostic accuracy estimates for COVID-19 RT-PCR and Lateral flow immunoassay tests with Bayesian latent class models

Diagnostic accuracy estimates for COVID-19 RT-PCR and Lateral flow immunoassay tests with Bayesian latent class models

Performance characteristics of five immunoassays for SARS-CoV-2: a head-to-head benchmark comparison

Quantifying antibody kinetics and RNA detection during early-phase SARS-CoV-2 infection by time since symptom onset

Contact Info

Product

Resources

About