Epidemiologic Characteristics Associated With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antigen-Based Test Results, Real-Time Reverse Transcription Polymerase Chain Reaction (rRT-PCR) Cycle Threshold Values, Subgenomic RNA, and Viral Culture Results From University Testing.

Abstract

BackgroundReal-time reverse transcription polymerase chain reaction (rRT-PCR) and antigen tests are important diagnostics for SARS-CoV-2. Sensitivity of antigen tests has been shown to be lower than that of rRT-PCR; however, data to evaluate epidemiologic characteristics that affect test performance are limited.MethodsPaired mid-turbinate nasal swabs were collected from university students and staff and tested for SARS-CoV-2 using both Quidel Sofia SARS Antigen Fluorescent Immunoassay (FIA) and rRT-PCR assay. Specimens positive by either rRT-PCR or antigen FIA were placed in viral culture and tested for subgenomic RNA (sgRNA). Logistic regression models were used to evaluate characteristics associated with antigen results, rRT-PCR cycle threshold (Ct) values, sgRNA, and viral culture.ResultsAntigen FIA sensitivity was 78.9% and 43.8% among symptomatic and asymptomatic participants respectively. Among rRT-PCR positive participants, negative antigen results were more likely among asymptomatic participants (OR 4.6, CI:1.3-15.4) and less likely among participants reporting nasal congestion (OR 0.1, CI:0.03-0.8). rRT-PCR-positive specimens with higher Ct values (OR 0.5, CI:0.4-0.8) were less likely, and specimens positive for sgRNA (OR 10.2, CI:1.6-65.0) more likely, to yield positive virus isolation. Antigen testing was >90% positive in specimens with Ct values <29. Positive predictive value of antigen test for positive viral culture (57.7%) was similar to that of rRT-PCR (59.3%).ConclusionsSARS-CoV-2 antigen test advantages include low cost, wide availability and rapid turnaround time, making them important screening tests. The performance of antigen tests may vary with patient characteristics, so performance characteristics should be accounted for when designing testing strategies and interpreting results.