Performance of three automated SARS-CoV-2 antibody assays and relevance of orthogonal testing algorithms

Clin Chem Lab Med. 2020 Nov 19;59(2):411-419. doi: 10.1515/cclm-2020-1378.


Objectives: Development and implementation of SARS-CoV-2 serologic assays gained momentum. Laboratories keep on investigating the performance of these assays. In this study, we compared three fully automated SARS-CoV-2 antibody assays.

Methods: A total of 186 samples from 84 PCR-positive COVID-19 patients and 120 control samples taken before the SARS-CoV-2 pandemic were analyzed using commercial serologic assays from Roche, Siemens and DiaSorin. Time after the positive COVID-19 PCR result and onset of symptoms was retrieved from the medical record. An extended golden standard, using the result of all three assays was defined, judging if antibodies are present or absent in a sample. Diagnostic and screening sensitivity/specificity and positive/negative predictive value were calculated.

Results: Diagnostic sensitivity (ability to detect a COVID-19 positive patient) ≥14 days after positive PCR testing was 96.7% (95% CI 88.5-99.6%) for DiaSorin, 93.3% (95% CI 83.8-98.2%) for Roche and 100% (95% CI 94.0-100%) for Siemens. Lower diagnostic sensitivities were observed <14 days after onset of symptoms for all three assay. Diagnostic specificity (ability to detect a COVID-19 negative patient) was 95.0% (95% CI 89.4-98.1%) for DiaSorin, 99.2% (95% CI 95.4-99.9%) for Roche and 100% (95% CI 97.0-100%) for Siemens. The sensitivity/specificity for detecting antibodies (ability of detecting absence (specificity) or presence (sensitivity) of COVID-19 antibodies) was 92.4% (95% CI 86.4-96.3%)/94.9% (95% CI 90.5-97.6%) for DiaSorin, 97.7% (95% CI 93.5-99.5%)/97.1% (95% CI 93.5-99.1%) for Roche and 98.5% (95% CI 94.6-99.8)/97.1 (95% CI 93.5-99.1%) for Siemens.

Conclusions: This study revealed acceptable performance for all three assays. An orthogonal testing algorithm using the Siemens and Roche assay achieved the highest positive predictive values for antibody detection in low seroprevalence settings.

Keywords: COVID-19; SARS-CoV-2; serology.

Publication types

  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Algorithms
  • Antibodies, Viral / blood*
  • Automation, Laboratory
  • COVID-19 / diagnosis*
  • COVID-19 / immunology
  • COVID-19 Serological Testing / methods
  • COVID-19 Serological Testing / statistics & numerical data
  • Female
  • Humans
  • Male
  • Middle Aged
  • Retrospective Studies
  • SARS-CoV-2 / immunology
  • Young Adult


  • Antibodies, Viral