Objectives
When SARS-CoV-2 prevalence is low, many positive test results are false positives. Confirmatory testing reduces overdiagnosis and nosocomial infection and enables real-world estimates of test specificity and positive predictive value. This study estimates these parameters to evaluate the impact of confirmatory testing, and to improve clinical diagnosis, epidemiological estimation and interpretation of vaccine trials.
Methods
Over one month, we took all respiratory samples from our laboratory with a patient’s first detection of SARS-CoV-2 RNA (Hologic Aptima SARS-CoV-2 assay or in-house RT-PCR platform), and repeated testing using two platforms. Samples were categorised by source, and by whether clinical details suggested COVID-19 or corroborative testing from another laboratory. We estimated specificity and positive predictive value using maximum likelihood-based approaches.
Results
Of 19,597 samples, SARS-CoV-2 RNA was detected in 107. 52 corresponded to first-time detection (0.27% of tests on samples without previous detection); further testing detected SARS-CoV-2 RNA ≥1 time (“confirmed”) in 29 (56%), and failed to detect SARS-CoV-2 RNA (“not confirmed”) in 23 (44%). Depending upon assumed parameters, point estimates for specificity and positive predictive value were 99.91%–99.98% and 61.8%–89.8% respectively using the Hologic Aptima SARS-CoV-2 assay, and 97.4%–99.1% and 20.1%–73.8% respectively using an in-house assay.
Conclusions
Nucleic acid amplification testing for SARS-CoV-2 is highly specific. Nevertheless, when prevalence is low a significant proportion of initially positive results fail to confirm and confirmatory testing substantially reduces false positive detections. Omitting additional testing in samples with higher prior detection probabilities focuses testing where clinically impactful and minimises delay.