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Leveraging of SARS-CoV-2 PCR Cycle Thresholds Values to Forecast COVID-19 Trends

Introduction: 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 mode...

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Autores principales: Yin, Nicolas, Dellicour, Simon, Daubie, Valery, Franco, Nicolas, Wautier, Magali, Faes, Christel, Van Cauteren, Dieter, Nymark, Liv, Hens, Niel, Gilbert, Marius, Hallin, Marie, Vandenberg, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8591051/
https://www.ncbi.nlm.nih.gov/pubmed/34790677
http://dx.doi.org/10.3389/fmed.2021.743988
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author Yin, Nicolas
Dellicour, Simon
Daubie, Valery
Franco, Nicolas
Wautier, Magali
Faes, Christel
Van Cauteren, Dieter
Nymark, Liv
Hens, Niel
Gilbert, Marius
Hallin, Marie
Vandenberg, Olivier
author_facet Yin, Nicolas
Dellicour, Simon
Daubie, Valery
Franco, Nicolas
Wautier, Magali
Faes, Christel
Van Cauteren, Dieter
Nymark, Liv
Hens, Niel
Gilbert, Marius
Hallin, Marie
Vandenberg, Olivier
author_sort Yin, Nicolas
collection PubMed
description Introduction: 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.
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spelling pubmed-85910512021-11-16 Leveraging of SARS-CoV-2 PCR Cycle Thresholds Values to Forecast COVID-19 Trends Yin, Nicolas Dellicour, Simon Daubie, Valery Franco, Nicolas Wautier, Magali Faes, Christel Van Cauteren, Dieter Nymark, Liv Hens, Niel Gilbert, Marius Hallin, Marie Vandenberg, Olivier Front Med (Lausanne) Medicine Introduction: 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. Frontiers Media S.A. 2021-11-01 /pmc/articles/PMC8591051/ /pubmed/34790677 http://dx.doi.org/10.3389/fmed.2021.743988 Text en Copyright © 2021 Yin, Dellicour, Daubie, Franco, Wautier, Faes, Van Cauteren, Nymark, Hens, Gilbert, Hallin and Vandenberg. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Yin, Nicolas
Dellicour, Simon
Daubie, Valery
Franco, Nicolas
Wautier, Magali
Faes, Christel
Van Cauteren, Dieter
Nymark, Liv
Hens, Niel
Gilbert, Marius
Hallin, Marie
Vandenberg, Olivier
Leveraging of SARS-CoV-2 PCR Cycle Thresholds Values to Forecast COVID-19 Trends
title Leveraging of SARS-CoV-2 PCR Cycle Thresholds Values to Forecast COVID-19 Trends
title_full Leveraging of SARS-CoV-2 PCR Cycle Thresholds Values to Forecast COVID-19 Trends
title_fullStr Leveraging of SARS-CoV-2 PCR Cycle Thresholds Values to Forecast COVID-19 Trends
title_full_unstemmed Leveraging of SARS-CoV-2 PCR Cycle Thresholds Values to Forecast COVID-19 Trends
title_short Leveraging of SARS-CoV-2 PCR Cycle Thresholds Values to Forecast COVID-19 Trends
title_sort leveraging of sars-cov-2 pcr cycle thresholds values to forecast covid-19 trends
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8591051/
https://www.ncbi.nlm.nih.gov/pubmed/34790677
http://dx.doi.org/10.3389/fmed.2021.743988
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