Hide metadata

dc.date.accessioned2022-01-29T16:11:32Z
dc.date.available2022-01-29T16:11:32Z
dc.date.created2021-11-16T11:16:37Z
dc.date.issued2021
dc.identifier.citationYin, Nicolas Dellicour, Simon Daubie, Valery Franco, Nicolas Wautier, Magali Faes, Christel Van Cauteren, Dieter Nymark, Liv Solvår Hens, Niel Gilbert, Marius Hallin, Marie Vandenberg, Oliver . Leveraging of SARS-CoV-2 PCR cycle thresholds values to forecast COVID-19 trends. Frontiers in medicine. 2021, 8:743988, 1-9
dc.identifier.urihttp://hdl.handle.net/10852/90288
dc.description.abstractIntroduction: We assessed the usefulness of SARS-CoV-2 RT-PCR cycle thresholds (Ct) values trends produced by the LHUB-ULB (a consolidated microbiology laboratory located in Brussels, Belgium) for monitoring the epidemic's dynamics at local and national levels and for improving forecasting models. Methods: SARS-CoV-2 RT-PCR Ct values produced from April 1, 2020, to May 15, 2021, were compared with national COVID-19 confirmed cases notifications according to their geographical and time distribution. These Ct values were evaluated against both a phase diagram predicting the number of COVID-19 patients requiring intensive care and an age-structured model estimating COVID-19 prevalence in Belgium. Results: Over 155,811 RT-PCR performed, 12,799 were positive and 7,910 Ct values were available for analysis. The 14-day median Ct values were negatively correlated with the 14-day mean daily positive tests with a lag of 17 days. In addition, the 14-day mean daily positive tests in LHUB-ULB were strongly correlated with the 14-day mean confirmed cases in the Brussels-Capital and in Belgium with coinciding start, peak, and end of the different waves of the epidemic. Ct values decreased concurrently with the forecasted phase-shifts of the diagram. Similarly, the evolution of 14-day median Ct values was negatively correlated with daily estimated prevalence for all age-classes. Conclusion: We provide preliminary evidence that trends of Ct values can help to both follow and predict the epidemic's trajectory at local and national levels, underlining that consolidated microbiology laboratories can act as epidemic sensors as they gather data that are representative of the geographical area they serve.
dc.languageEN
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleLeveraging of SARS-CoV-2 PCR cycle thresholds values to forecast COVID-19 trends
dc.typeJournal article
dc.creator.authorYin, Nicolas
dc.creator.authorDellicour, Simon
dc.creator.authorDaubie, Valery
dc.creator.authorFranco, Nicolas
dc.creator.authorWautier, Magali
dc.creator.authorFaes, Christel
dc.creator.authorVan Cauteren, Dieter
dc.creator.authorNymark, Liv Solvår
dc.creator.authorHens, Niel
dc.creator.authorGilbert, Marius
dc.creator.authorHallin, Marie
dc.creator.authorVandenberg, Oliver
cristin.unitcode185,52,11,0
cristin.unitnameAvdeling for helseledelse og helseøkonomi
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.cristin1955058
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Frontiers in medicine&rft.volume=8:743988&rft.spage=1&rft.date=2021
dc.identifier.jtitleFrontiers in medicine
dc.identifier.volume8
dc.identifier.doihttps://doi.org/10.3389/fmed.2021.743988
dc.identifier.urnURN:NBN:no-92888
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn2296-858X
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/90288/1/Yin_2022_Lev.pdf
dc.type.versionPublishedVersion
cristin.articleid743988
dc.relation.projectEC/H2020/682540
dc.relation.projectEC/H2020/101003688


Files in this item

Appears in the following Collection

Hide metadata

Attribution 4.0 International
This item's license is: Attribution 4.0 International