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Comparing the incidence of SARS-CoV-2 across age groups considering sampling biases - use of testing data of autumn 2021 in Belgium

BACKGROUND: To design efficient mitigation measures against COVID-19, understanding the transmission dynamics between different age groups was crucial. The role of children in the pandemic has been intensely debated and involves both scientific and ethical questions. To design efficient age-targeted...

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Autores principales: Lajot, Adrien, Cornelissen, Laura, Van Cauteren, Dieter, Meurisse, Marjan, Brondeel, Ruben, Dupont-Gillain, Christine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10122721/
https://www.ncbi.nlm.nih.gov/pubmed/37088854
http://dx.doi.org/10.1186/s13690-023-01072-9
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author Lajot, Adrien
Cornelissen, Laura
Van Cauteren, Dieter
Meurisse, Marjan
Brondeel, Ruben
Dupont-Gillain, Christine
author_facet Lajot, Adrien
Cornelissen, Laura
Van Cauteren, Dieter
Meurisse, Marjan
Brondeel, Ruben
Dupont-Gillain, Christine
author_sort Lajot, Adrien
collection PubMed
description BACKGROUND: To design efficient mitigation measures against COVID-19, understanding the transmission dynamics between different age groups was crucial. The role of children in the pandemic has been intensely debated and involves both scientific and ethical questions. To design efficient age-targeted non-pharmaceutical interventions (NPI), a good view of the incidence of the different age groups was needed. However, using Belgian testing data to infer real incidence (RI) from observed incidence (OI) or positivity ratio (PR) was not trivial. METHODS: Based on Belgian testing data collected during the Delta wave of Autumn 2021, we compared the use of different estimators of RI and analyzed their effect on comparisons between age groups. RESULTS: We found that the RI estimator’s choice strongly influences the comparison between age groups. CONCLUSION: The widespread implementation of testing campaigns using representative population samples could help to avoid pitfalls related to the current testing strategy in Belgium and worldwide. This approach would also allow a better comparison of the data from different countries while reducing biases arising from the specificities of each surveillance system.
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spelling pubmed-101227212023-04-24 Comparing the incidence of SARS-CoV-2 across age groups considering sampling biases - use of testing data of autumn 2021 in Belgium Lajot, Adrien Cornelissen, Laura Van Cauteren, Dieter Meurisse, Marjan Brondeel, Ruben Dupont-Gillain, Christine Arch Public Health Research BACKGROUND: To design efficient mitigation measures against COVID-19, understanding the transmission dynamics between different age groups was crucial. The role of children in the pandemic has been intensely debated and involves both scientific and ethical questions. To design efficient age-targeted non-pharmaceutical interventions (NPI), a good view of the incidence of the different age groups was needed. However, using Belgian testing data to infer real incidence (RI) from observed incidence (OI) or positivity ratio (PR) was not trivial. METHODS: Based on Belgian testing data collected during the Delta wave of Autumn 2021, we compared the use of different estimators of RI and analyzed their effect on comparisons between age groups. RESULTS: We found that the RI estimator’s choice strongly influences the comparison between age groups. CONCLUSION: The widespread implementation of testing campaigns using representative population samples could help to avoid pitfalls related to the current testing strategy in Belgium and worldwide. This approach would also allow a better comparison of the data from different countries while reducing biases arising from the specificities of each surveillance system. BioMed Central 2023-04-23 /pmc/articles/PMC10122721/ /pubmed/37088854 http://dx.doi.org/10.1186/s13690-023-01072-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Lajot, Adrien
Cornelissen, Laura
Van Cauteren, Dieter
Meurisse, Marjan
Brondeel, Ruben
Dupont-Gillain, Christine
Comparing the incidence of SARS-CoV-2 across age groups considering sampling biases - use of testing data of autumn 2021 in Belgium
title Comparing the incidence of SARS-CoV-2 across age groups considering sampling biases - use of testing data of autumn 2021 in Belgium
title_full Comparing the incidence of SARS-CoV-2 across age groups considering sampling biases - use of testing data of autumn 2021 in Belgium
title_fullStr Comparing the incidence of SARS-CoV-2 across age groups considering sampling biases - use of testing data of autumn 2021 in Belgium
title_full_unstemmed Comparing the incidence of SARS-CoV-2 across age groups considering sampling biases - use of testing data of autumn 2021 in Belgium
title_short Comparing the incidence of SARS-CoV-2 across age groups considering sampling biases - use of testing data of autumn 2021 in Belgium
title_sort comparing the incidence of sars-cov-2 across age groups considering sampling biases - use of testing data of autumn 2021 in belgium
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10122721/
https://www.ncbi.nlm.nih.gov/pubmed/37088854
http://dx.doi.org/10.1186/s13690-023-01072-9
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