Abstract
BackgroundThe COVID-19 pandemic has led to an unprecedented daily use of RT-PCR tests. These tests are interpreted qualitatively for diagnosis, and the relevance of the test result intensity, i.e. the number of quantification cycles (Cq), is debated because of strong potential biases.AimWe explored the possibility to use Cq values from SARS-CoV-2 screening tests to better understand the spread of an epidemic and to better understand the biology of the infection.MethodsWe used linear regression models to analyse a large database of 793,479 Cq values from tests performed on more than 2 million samples between 21 January and 30 November 2020, i.e. the first two pandemic waves. We performed time series analysis using autoregressive integrated moving average (ARIMA) models to estimate whether Cq data information improves short-term predictions of epidemiological dynamics.ResultsAlthough we found that the Cq values varied depending on the testing laboratory or the assay used, we detected strong significant trends associated with patient age, number of days after symptoms onset or the state of the epidemic (the temporal reproduction number) at the time of the test. Furthermore, knowing the quartiles of the Cq distribution greatly reduced the error in predicting the temporal reproduction number of the COVID-19 epidemic.ConclusionOur results suggest that Cq values of screening tests performed in the general population generate testable hypotheses and help improve short-term predictions for epidemic surveillance.
Highlights
Molecular testing is a key component of screening policies to control the spread of infectious diseases, and the coronavirus disease (COVID-19) pandemic has led to an unprecedented testing rate using reverse transcription PCR (RT-PCR) assays [1]
Care should be taken in the interpretation given that the data were unbalanced, which is why we performed an analysis of variance (ANOVA) with type II sums of squares
All factors except the reproduction number (Rt) were significantly associated with Cq values using a classical 5% p value criterion
Summary
Molecular testing is a key component of screening policies to control the spread of infectious diseases, and the coronavirus disease (COVID-19) pandemic has led to an unprecedented testing rate using reverse transcription PCR (RT-PCR) assays [1]. In clinical and public health practice, RT-PCR results are qualitative for viral respiratory disease diagnostics, with reports such as ‘positive’, ‘negative’, ‘uninterpretable’ and, sometimes, ‘weakly positive’ These are based on the cycles threshold, referred to as crossing point or crossing threshold (here denoted quantification cycles (Cq)), which corresponds to the number of PCR amplification cycles required for the fluorescent signal to rise above a positive threshold. The more abundant the genetic target in the sample, the fewer the amplification cycles required to detect it This is why numerous studies on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rely on Cq values to assess transmissibility [2] or study infection kinetics [3]. Conclusion: Our results suggest that Cq values of screening tests performed in the general population
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