Evaluation of serological tests for SARS-CoV-2: Implications for serology testing in a low-prevalence setting

Abstract

Background: Robust serological assays are essential for long-term control of the COVID-19 pandemic. Many recently released point-of-care (PoCT) serological assays have been distributed with little pre-market validation. Methods: Performance characteristics for five PoCT lateral flow devices approved for use in Australia were compared to a commercial enzyme immunoassay (ELISA) and a recently described novel surrogate virus neutralisation test (sVNT). Results: Sensitivities for PoCT ranged from 51.8% (95% CI 43.1 to 60.4%) to 67.9% (95% CI 59.4-75.6%), and specificities from 95.6% (95% CI 89.2-98.8%) to 100.0% (95% CI 96.1-100.0%). Overall ELISA sensitivity for either IgA or IgG detection was 67.9% (95% CI 59.4-75.6), increasing to 93.8% (95% CI 85.0-98.3%) for samples >14 days post symptom onset. Overall, sVNT sensitivity was 60.9% (95% CI 53.2-68.4%), rising to 91.2%% (95% CI 81.8-96.7%) for samples collected >14 days post-symptom onset, with a specificity 94.4% (95% CI 89.2-97.5%), Conclusion: Performance characteristics for COVID-19 serological assays were generally lower than those reported by manufacturers. Timing of specimen collection relative to onset of illness or infection is crucial in the reporting of performance characteristics for COVID-19 serological assays. The optimal algorithm for implementing serological testing for COVID-19 remains to be determined, particularly in low-prevalence settings.

Estimating unobserved SARS-CoV-2 infections in the United States

“…Although other approaches—namely, serological surveys—could have provided more direct answers to the question of how many unobserved infections there were in the weeks following the arrival of SARS-CoV-2 in the United States, serological assays were only beginning to be developed at that time ( 35 ). Even now that results from serological surveys are beginning to emerge ( 36 ), they still do not address the extent of unobserved infections during the specific time frame of our analysis, are not representative of the United States as a whole, and can be sensitive to even small inaccuracies in assay performance ( 37 , 38 ). Relative to other approaches, our approach offers the ability to quickly obtain provisional estimates of the number of unobserved infections early in an epidemic, when there still might be time to act on that information with testing and case isolation.…”

Low postpandemic wave SARS‐CoV‐2 seroprevalence in Kuala Lumpur and Selangor, Malaysia

“…Samples were first screened with an in-house indirect enzymelinked immunosorbent assay (ELISA) detecting IgG to SARS-CoV-2 receptor binding domain (RBD), and shown to be 100% sensitive for samples collected from 14 days postonset of illness. 3 Screenseropositive samples were confirmed with a highly sensitive and specific (99.3%-100%) surrogate viral neutralization test (sVNT; cPass, Gen-Script) based on total antibody-mediated blockage of angiotensinconverting enzyme 2 receptor-RBD interaction, 4,5 which has received provisional authorization from the Singapore Health Sciences Authority.A two-step testing process of screening with a highly sensitive assay and confirmation with a highly specific assay is useful for low-prevalence settings where seropositives have a low predictive value 5. These two assays were evaluated in our laboratory with the 228 (ELISA) or 26 (sVNT) prepandemic serum samples as negative controls and 35 samples collected from PCR-confirmed patients with COVID-19 at least 16 days post-onset of illness.…”

Antibody testing for coronavirus disease 2019: not ready for prime time

“…It is unlikely that any single serologic test will provide the kind of reliable and accurate information that are needed to fully understand the current pandemic. As Bastos and colleagues and others have indicated,5 tests with low specificity provide more false positives than true positives in low prevalence settings, resulting in unacceptably low positive predictive values. To overcome the poor performance of a single serologic test, an algorithm should be considered that combines two or more tests (eg,6).…”