Performance Decay of Molecular Assays Near the Limit of Detection: Probabilistic Modeling using Real-World COVID-19 Data

ABSTRACT The gold standard for diagnosis of COVID-19 is detection of SARS-CoV-2 RNA by RT-PCR. However, the effect of systematic changes in specimen viral burden on the overall assay performance is not quantitatively described. We observed decreased viral burdens in our testing population as the pandemic progressed, with median sample Ct values increasing from 22.7 to 32.8 from weeks 14 and 20, respectively. We developed a method using computer simulations to quantify the implications of variable SARS-CoV-2 viral burden on observed assay performance. We found that overall decreasing viral burden can have profound effects on assay detection rates. When real-world Ct values were used as source data in a bootstrap resampling simulation, the sensitivity of the same hypothetical assay decreased from 97.59 (95% CI 97.3-97.9) in week 12, to 74.42 (95% CI 73.9-75) in week 20. Furthermore, simulated assays with a 3-fold or 10-fold reduced sensitivity would both appear to be >95% sensitive early in the pandemic, but sensitivity would fall to 85.55 (95% CI 84.9-86.2) and 74.38 (95% CI 73.6-75.1) later in the pandemic, respectively. Our modeling approach can be used to better quantitate the impact that specimen viral burden may have on the clinical application of tests and specimens.