Evaluation and Modelling of the Performance of an Automated SARS-CoV-2 Antigen Assay According to Sample Type, Target Population and Epidemic Trends
Nicolas Yin,
Cyril Debuysschere,
Valery Daubie,
Marc Hildebrand,
Charlotte Martin,
Sonja Curac,
Fanny Ponthieux,
Marie-Christine Payen,
Olivier Vandenberg,
Marie Hallin
Affiliations
Nicolas Yin
Department of Microbiology, Laboratoire Hospitalier Universitaire de Bruxelles-Universitair Laboratorium Brussel (LHUB-ULB), Université Libre de Bruxelles (ULB), 1000 Brussels, Belgium
Cyril Debuysschere
Department of Microbiology, Laboratoire Hospitalier Universitaire de Bruxelles-Universitair Laboratorium Brussel (LHUB-ULB), Université Libre de Bruxelles (ULB), 1000 Brussels, Belgium
Valery Daubie
Department of Microbiology, Laboratoire Hospitalier Universitaire de Bruxelles-Universitair Laboratorium Brussel (LHUB-ULB), Université Libre de Bruxelles (ULB), 1000 Brussels, Belgium
Marc Hildebrand
Department of Internal Medicine, Erasme University Hospital, Université Libre de Bruxelles (ULB), 1070 Brussels, Belgium
Charlotte Martin
Department of Infectious Diseases, Saint-Pierre University Hospital, Université Libre de Bruxelles (ULB), 1000 Brussels, Belgium
Sonja Curac
Emergency Department, Erasme University Hospital, Université Libre de Bruxelles (ULB), 1070 Brussels, Belgium
Fanny Ponthieux
Department of Microbiology, Laboratoire Hospitalier Universitaire de Bruxelles-Universitair Laboratorium Brussel (LHUB-ULB), Université Libre de Bruxelles (ULB), 1000 Brussels, Belgium
Marie-Christine Payen
Department of Infectious Diseases, Saint-Pierre University Hospital, Université Libre de Bruxelles (ULB), 1000 Brussels, Belgium
Olivier Vandenberg
Centre for Environmental Health and Occupational Health, School of Public Health, Université Libre de Bruxelles (ULB), 1050 Brussels, Belgium
Marie Hallin
Department of Microbiology, Laboratoire Hospitalier Universitaire de Bruxelles-Universitair Laboratorium Brussel (LHUB-ULB), Université Libre de Bruxelles (ULB), 1000 Brussels, Belgium
The Lumipulse® G SARS-CoV-2 Ag assay performance was evaluated on prospectively collected saliva and nasopharyngeal swabs (NPS) of recently ill in- and outpatients and according to the estimated viral load. Performances were calculated using RT-PCR positive NPS from patients with symptoms ≤ 7 days and RT-PCR negative NPS as gold standard. In addition, non-selected positive NPS were analyzed to assess the performances on various viral loads. This assay yielded a sensitivity of 93.1% on NPS and 71.4% on saliva for recently ill patients. For NPS with a viral load > 103 RNA copies/mL, sensitivity was 96.4%. A model established on our daily routine showed fluctuations of the performances depending on the epidemic trends but an overall good negative predictive value. Lumipulse® G SARS-CoV-2 assay yielded good performance for an automated antigen detection assay on NPS. Using it for the detection of recently ill patients or to screen high-risk patients could be an interesting alternative to the more expensive RT-PCR.