Utilization of hantavirus antibody results generated over a five‐year period to develop an improved serologic algorithm for detecting acute Sin Nombre hantavirus infection

Abstract

In the United States most cases of hantavirus pulmonary syndrome (HPS) are caused by the Sin Nombre virus (SNV) and are typically identified by serology. The goal of this study was to assess the performance of our hantavirus serologic testing algorithm by reviewing results generated over five years. Sera were screened for pan-hantavirus immunoglobulin (Ig)G and IgM by enzyme-linked immunosorbent assay (ELISA). Screen IgG+ sera were then tested by immunoblot for SNV glycoprotein-specific IgG, and screen IgM+ sera were tested for SNV-specific IgM using an ELISA that measured differential reactivity to SNV and Seoul nucleocapsid proteins. Although only 13% of sera were positive in one or both screening assays, 85% of screen+sera lacked SNV antibodies. Nearly all (97%) screen IgM-IgG+ samples lacked SNV IgG, and 90% of screen IgM+IgG- samples lacked SNV IgM. However, SNV IgM testing of screen IgM+IgG- samples appears to be necessary, since this test identified nine of 37 patients with acute HPS (based on clinical feedback). A screen IgM+IgG+ result was a good predictor of SNV antibody detection and acute HPS. These findings were used to design a modified algorithm that identified all 37 patients with acute HPS, but reduced the number of specimens that required SNV antibody testing by 42%.