ABSTRACT
BackgroundRoutine testing for SARS-CoV-2 in the community is essential for guiding key epidemiological decisions from the quarantine of individual patients to enrolling regional and national preventive measures. Yet, the primary testing tool, the RT-qPCR based testing, is notoriously known for its low sensitivity, i.e. high risk of missed detection of carriers. Quantifying the false-negative rate (FNR) of the RT-qPCR test at the community settings and its dependence on patient demographic and disease progression is therefore key in designing and refining strategies for disease spread prevention. MethodsAnalyzing 843,917 test results of 521,696 patients, we identified false-negative (FN) and true-positive (TP) results as negative and positive results preceded by a COVID-19 diagnosis and followed by a later positive test. Regression analyses were used to determine associations of false-negative results with time of sampling after diagnosis, patient demographics and viral loads based on RT-qPCR Ct values of the next positive tests. FindingsThe overall FNR was 22.8%, which is consistent with previous studies. Yet, this rate was much lower at the first 5 days following diagnosis (10.7%) and only increased in later dates. Furthermore, the FNR was strongly associated with demographics, with odds ratio of 1.74 (95% CI: 1.58-1.90) for women over men and 1.36 (95% CI: 1.34-1.39) for 10 years younger patients. Finally, FNR was associated with viral loads (p-value 0.0005), with a difference of 1.50 (95% CI: 0.70-2.30) between the average Ct of the N gene in a positive test following a false-negative compared to a positive test following a true-positive. InterpretationOur results show that in the first few days following diagnosis, when results are critical for quarantine decisions, RT-qPCR testing is more reliable than previously reported. Yet the reliability of the test result is reduced in later days as well as for women and younger patients, where the viral loads are typically lower. FundingThis research was supported by the ISRAEL SCIENCE FOUNDATION (grant No. 3633/19) within the KillCorona - Curbing Coronavirus Research Program.
