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Quantifying and communicating the burden of COVID-19

BACKGROUND: An essential aspect of preventing further COVID-19 outbreaks and to learn for future pandemics is the evaluation of different political strategies, which aim at reducing transmission of and mortality due to COVID-19. One important aspect in this context is the comparison of attributable...

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Autores principales: von Cube, Maja, Timsit, Jéan-Francois, Kammerlander, Andreas, Schumacher, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353440/
https://www.ncbi.nlm.nih.gov/pubmed/34376146
http://dx.doi.org/10.1186/s12874-021-01349-z
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author von Cube, Maja
Timsit, Jéan-Francois
Kammerlander, Andreas
Schumacher, Martin
author_facet von Cube, Maja
Timsit, Jéan-Francois
Kammerlander, Andreas
Schumacher, Martin
author_sort von Cube, Maja
collection PubMed
description BACKGROUND: An essential aspect of preventing further COVID-19 outbreaks and to learn for future pandemics is the evaluation of different political strategies, which aim at reducing transmission of and mortality due to COVID-19. One important aspect in this context is the comparison of attributable mortality. METHODS: We give a comprehensive overview of six epidemiological measures that are used to quantify COVID-19 attributable mortality (p-score, standardized mortality ratio, absolute number of excess deaths, per capita rate, z-score and the population attributable fraction). RESULTS: By defining the six measures based on observed and expected deaths, we explain their relationship. Moreover, three publicly available data examples serve to illustrate the interpretational strengths and weaknesses of the various measures. Finally, we give recommendation which measures are suitable for an evaluation of public health strategies against COVID-19. The R code to reproduce the results is available as online supplementary material. CONCLUSION: The number of excess deaths should be always reported together with the population attributable fraction, the p-score or the standardized mortality ratio instead of a per capita rate. For a complete picture of COVID-19 attributable mortality, quantifying and communicating its relative burden also to a lay audience is of major importance. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01349-z.
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spelling pubmed-83534402021-08-10 Quantifying and communicating the burden of COVID-19 von Cube, Maja Timsit, Jéan-Francois Kammerlander, Andreas Schumacher, Martin BMC Med Res Methodol Research BACKGROUND: An essential aspect of preventing further COVID-19 outbreaks and to learn for future pandemics is the evaluation of different political strategies, which aim at reducing transmission of and mortality due to COVID-19. One important aspect in this context is the comparison of attributable mortality. METHODS: We give a comprehensive overview of six epidemiological measures that are used to quantify COVID-19 attributable mortality (p-score, standardized mortality ratio, absolute number of excess deaths, per capita rate, z-score and the population attributable fraction). RESULTS: By defining the six measures based on observed and expected deaths, we explain their relationship. Moreover, three publicly available data examples serve to illustrate the interpretational strengths and weaknesses of the various measures. Finally, we give recommendation which measures are suitable for an evaluation of public health strategies against COVID-19. The R code to reproduce the results is available as online supplementary material. CONCLUSION: The number of excess deaths should be always reported together with the population attributable fraction, the p-score or the standardized mortality ratio instead of a per capita rate. For a complete picture of COVID-19 attributable mortality, quantifying and communicating its relative burden also to a lay audience is of major importance. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01349-z. BioMed Central 2021-08-10 /pmc/articles/PMC8353440/ /pubmed/34376146 http://dx.doi.org/10.1186/s12874-021-01349-z Text en © The Author(s) 2021 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
von Cube, Maja
Timsit, Jéan-Francois
Kammerlander, Andreas
Schumacher, Martin
Quantifying and communicating the burden of COVID-19
title Quantifying and communicating the burden of COVID-19
title_full Quantifying and communicating the burden of COVID-19
title_fullStr Quantifying and communicating the burden of COVID-19
title_full_unstemmed Quantifying and communicating the burden of COVID-19
title_short Quantifying and communicating the burden of COVID-19
title_sort quantifying and communicating the burden of covid-19
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353440/
https://www.ncbi.nlm.nih.gov/pubmed/34376146
http://dx.doi.org/10.1186/s12874-021-01349-z
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