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Serological SARS-CoV-2 assays are needed to support clinical diagnosis and epidemiological investigations. Recently, assays for large-scale detection of total antibodies (total-Ab) and immunoglobulin (Ig) G and M against SARS-CoV-2 antigens have been developed, but there are limited data on the diagnostic accuracy of these assays. This study was a Danish national collaboration and evaluated fifteen commercial and one in-house anti-SARS-CoV-2 assays in sixteen laboratories. Sensitivity was evaluated using 150 samples from individuals with asymptomatic, mild or moderate COVID-19; nonhospitalized or hospitalized, confirmed by nucleic acid amplification tests (NAAT), collected 13-73 days either from symptom onset or from positive NAAT (patients without symptoms). Specificity and cross reactivity were evaluated in samples collected prior to the SARS-CoV-2 epidemic from >586 blood donors and patients with autoimmune diseases, cytomegalovirus or Epstein-Barr virus infections and acute viral infections. A specificity of ≥99% was achieved by all total-Ab and IgG assays except one, Diasorin/LiaisonXL-IgG (97.2%). Sensitivities in descending order were: Wantai/ELISA total-Ab (96.7%), CUH-NOVO/in-house ELISA total-Ab (96.0%), Ortho/Vitros total-Ab (95.3%), YHLO/iFlash-IgG (94.0%), Ortho/Vitros-IgG (93.3%), Siemens/Atellica total-Ab (93.2%), Roche/Elecsys total-Ab (92.7%), Abbott/Architect-IgG (90.0%), Abbott/Alinity-IgG (median 88.0%), Diasorin/LiaisonXL-IgG (median 84.6%), Siemens/Vista total-Ab (81.0%), Euroimmun/ELISA-IgG (78.0%), and Snibe/Maglumi-IgG (median 78.0%). However, confidence intervals overlapped for several assays. The IgM results were variable, with the Wantai/ELISA-IgM showing the highest sensitivity (82.7%) and specificity (99%). The rate of seropositivity increased with time from symptom onset and symptom severity.

Based on symptoms and clinical findings at arrival, incidence rates of patients admitted to a medical emergency department with sepsis and severe sepsis are more frequent than previously reported based on discharge diagnoses.

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