Robust SARS-COV-2 serological population screens via multi-antigen rules-based approach

More than 300 SARS-COV-2 serological tests have recently been developed using either the nucleocapsid phosphoprotein (N), the spike glycoprotein subunit (S1), and more recently the receptor binding domain (RBD). Most of the assays report very good clinical performance characteristics in well-controlled clinical settings. However, there is a growing belief that good performance characteristics that are obtained during clinical performance trials might not be sufficient to deliver good diagnostic results in population-wide screens that are usually characterized with low seroprevalence. In this paper, we developed a serological assay against N, S1 and RBD using a bead-based multiplex platform and a rules-based computational approach to assess the performance of single and multi-antigen readouts in well-defined clinical samples and in a population-wide serosurvey from blood donors. Even though assays based on single antigen readouts performed similarly well in the clinical samples, there was a striking difference between the antigens on the population-wide screen. Asymptomatic individuals with low antibody titers and sub-optimal assay specificity might contribute to the large discrepancies in population studies with low seroprevalence. A multi-antigen assay requiring partial agreement between RBD, N and S1 readouts exhibited enhanced specificity, less dependency on assay cut-off values and an overall more robust performance in both sample settings. Our data suggest that assays based on multiple antigen readouts combined with a rules-based computational consensus can provide a more robust platform for routine antibody screening.