Increasing test specificity without impairing sensitivity: lessons learned from SARS-CoV-2 serology.

BACKGROUND: Serological tests are widely used in various medical disciplines for diagnostic and monitoring purposes. Unfortunately, the sensitivity and specificity of test systems are often poor, leaving room for false-positive and false-negative results. However, conventional methods were used to increase specificity and decrease sensitivity and vice versa. Using SARS-CoV-2 serology as an example, we propose here a novel testing strategy: the 'sensitivity improved two-test' or 'SIT²' algorithm. METHODS: SIT² involves confirmatory retesting of samples with results falling in a predefined retesting zone of an initial screening test, with adjusted cut-offs to increase sensitivity. We verified and compared the performance of SIT² to single tests and orthogonal testing (OTA) in an Austrian cohort (1117 negative, 64 post-COVID-positive samples) and validated the algorithm in an independent British cohort (976 negatives and 536 positives). RESULTS: The specificity of SIT² was superior to single tests and non-inferior to OTA. The sensitivity was maintained or even improved using SIT² when compared with single tests or OTA. SIT² allowed correct identification of infected individuals even when a live virus neutralisation assay could not detect antibodies. Compared with single testing or OTA, SIT² significantly reduced total test errors to 0.46% (0.24-0.65) or 1.60% (0.94-2.38) at both 5% or 20% seroprevalence. CONCLUSION: For SARS-CoV-2 serology, SIT² proved to be the best diagnostic choice at both 5% and 20% seroprevalence in all tested scenarios. It is an easy to apply algorithm and can potentially be helpful for the serology of other infectious diseases.

Low SARS-CoV-2 seroprevalence in the Austrian capital after an early governmental lockdown.

We analyzed SARS-CoV-2 seroprevalence in a large, well-described representative Viennese cohort after an early governmental lockdown with respect to the occurrence of symptoms and household transmission. Participants of the LEAD Study, a population-based cohort study from Vienna, Austria, were invited along with their household members (April 20th to May20th 2020). Sera were analyzed using anti-SARS-CoV-2 immunoassay including a neutralization test as a confirmatory assay. A total of 12,419 individuals participated (5984 LEAD participants; 6435 household members), 163 (1.31%; 59 LEAD cohort members) of whom were SARS-CoV-2 antibody positive. The estimated number of COVID-19 cases projected from our findings by age and sex for Vienna was 21,504 (1.13%). Cumulative number of positively tested cases in Vienna until May 20th 2020 was 3020, hence 7.1 times (95% confidence interval 5.5-9.1) lower than projected. Relative risk (RR) of seropositivity by age was highest for children aged 6-9 years [RR compared to age group 20-49: 1.21 (CI 0.37-4.01)], lowest for ≥ 65 years [RR 0.47 (CI 0.21-1.03)]. Half of the positive individuals developed no or mild symptoms. In a multivariate analysis, taste and smell disturbances were most strongly related to SARS-CoV-2 positivity. Infection probability within households with one confirmed SARS-CoV-2-specific antibody-positive person was 31%. Although seroprevalence was very low (1.13%) for a central European capital city, due to an early governmental lockdown, SARS-CoV-2 infections were more prevalent than officially reported polymerase chain reaction-positive cases. Of note, seroprevalence was highest in young children. Half of SARS-CoV-2 antibody-positive subjects had no or only mild symptoms. Taste and smell disturbances were most prominent, possibly guiding clinicians in diagnosing SARS-CoV-2 infection.

Side-by-Side Comparison of Three Fully Automated SARS-CoV-2 Antibody Assays with a Focus on Specificity.

BACKGROUND: In the context of the COVID-19 pandemic, numerous new serological test systems for the detection of anti-SARS-CoV-2 antibodies rapidly have become available. However, the clinical performance of many of these is still insufficiently described. Therefore, we compared 3 commercial CE-marked, SARS-CoV-2 antibody assays side by side. METHODS: We included a total of 1154 specimens from pre-COVID-19 times and 65 samples from COVID-19 patients (≥14 days after symptom onset) to evaluate the test performance of SARS-CoV-2 serological assays by Abbott, Roche, and DiaSorin. RESULTS: All 3 assays presented with high specificities: 99.2% (98.6-99.7) for Abbott, 99.7% (99.2-100.0) for Roche, and 98.3% (97.3-98.9) for DiaSorin. In contrast to the manufacturers' specifications, sensitivities only ranged from 83.1% to 89.2%. Although the 3 methods were in good agreement (Cohen's Kappa 0.71-0.87), McNemar tests revealed significant differences between results obtained from Roche and DiaSorin. However, at low seroprevalences, the minor differences in specificity resulted in profound discrepancies of positive predictive values at 1% seroprevalence: 52.3% (36.2-67.9), 77.6% (52.8-91.5), and 32.6% (23.6-43.1) for Abbott, Roche, and DiaSorin, respectively. CONCLUSION: We found diagnostically relevant differences in specificities for the anti-SARS-CoV-2 antibody assays by Abbott, Roche, and DiaSorin that have a significant impact on the positive predictive values of these tests.