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Epidemiological and clinical insights from SARS-CoV-2 RT-PCR crossing threshold values, France, January to November 2020

dc.rights.licenseopenen_US
dc.contributor.authorALIZON, Samuel
dc.contributor.authorSELINGER, Christian
dc.contributor.authorSOFONEA, Mircea
dc.contributor.authorHAIM-BOUKOBZA, Stéphanie
dc.contributor.authorGIANNOLI, Jean-Marc
dc.contributor.authorNINOVE, Laetitia
dc.contributor.authorPILLET, Sylvie
dc.contributor.authorTHIBAULT, V.
dc.contributor.authorDE ROUGEMONT, Alexis
hal.structure.identifierMicrobiologie Fondamentale et Pathogénicité [MFP]
dc.contributor.authorTUMIOTTO, Camille
dc.contributor.authorSTEPHAN, Robin
dc.contributor.authorBRESSOLLETTE-BODIN, Céline
dc.contributor.authorSALMONA, Maud
dc.contributor.authorL’HONNEUR, Anne-Sophie
dc.contributor.authorBEHILLIL, Sylvie
dc.contributor.authorLEFEUVRE, Caroline
dc.contributor.authorDINA, Julia
dc.contributor.authorHANTZ, Sébastien
dc.contributor.authorHARTARD, Cédric
dc.contributor.authorVEYER, David
dc.contributor.authorDELAGRÈVERIE, Héloïse
dc.contributor.authorFOURATI, Slim
dc.contributor.authorVISSEAUX, Benoît
dc.contributor.authorHENQUELL, Cécile
dc.contributor.authorLINA, Bruno
dc.contributor.authorFOULONGNE, Vincent
dc.contributor.authorBURREL, Sonia
dc.date.accessioned2023-05-16T15:13:58Z
dc.date.available2023-05-16T15:13:58Z
dc.date.issued2022
dc.identifier.issn1560-7917en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/182163
dc.description.abstractEnBackgroundThe 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.
dc.language.isoENen_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.title.enEpidemiological and clinical insights from SARS-CoV-2 RT-PCR crossing threshold values, France, January to November 2020
dc.typeArticle de revueen_US
dc.identifier.doi10.2807/1560-7917.ES.2022.27.6.2100406en_US
dc.subject.halInformatique [cs]/Modélisation et simulationen_US
dc.subject.halSciences de l'environnement/Biodiversité et Ecologieen_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.subject.halSciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]en_US
dc.subject.halSciences du Vivant [q-bio]/Biodiversité/Evolution [q-bio.PE]en_US
dc.subject.halSciences du Vivant [q-bio]/Biodiversité/Systématique, phylogénie et taxonomieen_US
dc.subject.halSciences du Vivant [q-bio]/Ecologie, Environnement/Ecosystèmesen_US
dc.subject.halSciences du Vivant [q-bio]/Ecologie, Environnement/Interactions entre organismesen_US
dc.subject.halSciences du Vivant [q-bio]/Ecologie, Environnement/Santéen_US
dc.subject.halSciences du Vivant [q-bio]/Génétique/Génétique des populations [q-bio.PE]en_US
dc.subject.halSciences du Vivant [q-bio]/Microbiologie et Parasitologie/Virologieen_US
bordeaux.journalEurosurveillanceen_US
bordeaux.page2100406en_US
bordeaux.volume27en_US
bordeaux.hal.laboratoriesMFP (Laboratoire Microbiologie Fondamentale et Pathogénicité) - UMR 5234en_US
bordeaux.issue6en_US
bordeaux.institutionCNRSen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.import.sourcehal
hal.identifierhal-03175551
hal.version1
hal.exportfalse
workflow.import.sourcehal
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Eurosurveillance&rft.date=2022&rft.volume=27&rft.issue=6&rft.spage=2100406&rft.epage=2100406&rft.eissn=1560-7917&rft.issn=1560-7917&rft.au=ALIZON,%20Samuel&SELINGER,%20Christian&SOFONEA,%20Mircea&HAIM-BOUKOBZA,%20St%C3%A9phanie&GIANNOLI,%20Jean-Marc&rft.genre=article


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