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Estimating the effects of non-pharmaceutical interventions on the number of new infections with COVID-19 during the first epidemic wave

The novel coronavirus (SARS-CoV-2) has rapidly developed into a global epidemic. To control its spread, countries have implemented non-pharmaceutical interventions (NPIs), such as school closures, bans of small gatherings, or even stay-at-home orders. Here we study the effectiveness of seven NPIs in...

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Autores principales: Banholzer, Nicolas, van Weenen, Eva, Lison, Adrian, Cenedese, Alberto, Seeliger, Arne, Kratzwald, Bernhard, Tschernutter, Daniel, Salles, Joan Puig, Bottrighi, Pierluigi, Lehtinen, Sonja, Feuerriegel, Stefan, Vach, Werner
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8171941/
https://www.ncbi.nlm.nih.gov/pubmed/34077448
http://dx.doi.org/10.1371/journal.pone.0252827
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author Banholzer, Nicolas
van Weenen, Eva
Lison, Adrian
Cenedese, Alberto
Seeliger, Arne
Kratzwald, Bernhard
Tschernutter, Daniel
Salles, Joan Puig
Bottrighi, Pierluigi
Lehtinen, Sonja
Feuerriegel, Stefan
Vach, Werner
author_facet Banholzer, Nicolas
van Weenen, Eva
Lison, Adrian
Cenedese, Alberto
Seeliger, Arne
Kratzwald, Bernhard
Tschernutter, Daniel
Salles, Joan Puig
Bottrighi, Pierluigi
Lehtinen, Sonja
Feuerriegel, Stefan
Vach, Werner
author_sort Banholzer, Nicolas
collection PubMed
description The novel coronavirus (SARS-CoV-2) has rapidly developed into a global epidemic. To control its spread, countries have implemented non-pharmaceutical interventions (NPIs), such as school closures, bans of small gatherings, or even stay-at-home orders. Here we study the effectiveness of seven NPIs in reducing the number of new infections, which was inferred from the reported cases of COVID-19 using a semi-mechanistic Bayesian hierarchical model. Based on data from the first epidemic wave of n = 20 countries (i.e., the United States, Canada, Australia, the EU-15 countries, Norway, and Switzerland), we estimate the relative reduction in the number of new infections attributed to each NPI. Among the NPIs considered, bans of large gatherings were most effective, followed by venue and school closures, whereas stay-at-home orders and work-from-home orders were least effective. With this retrospective cross-country analysis, we provide estimates regarding the effectiveness of different NPIs during the first epidemic wave.
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spelling pubmed-81719412021-06-14 Estimating the effects of non-pharmaceutical interventions on the number of new infections with COVID-19 during the first epidemic wave Banholzer, Nicolas van Weenen, Eva Lison, Adrian Cenedese, Alberto Seeliger, Arne Kratzwald, Bernhard Tschernutter, Daniel Salles, Joan Puig Bottrighi, Pierluigi Lehtinen, Sonja Feuerriegel, Stefan Vach, Werner PLoS One Research Article The novel coronavirus (SARS-CoV-2) has rapidly developed into a global epidemic. To control its spread, countries have implemented non-pharmaceutical interventions (NPIs), such as school closures, bans of small gatherings, or even stay-at-home orders. Here we study the effectiveness of seven NPIs in reducing the number of new infections, which was inferred from the reported cases of COVID-19 using a semi-mechanistic Bayesian hierarchical model. Based on data from the first epidemic wave of n = 20 countries (i.e., the United States, Canada, Australia, the EU-15 countries, Norway, and Switzerland), we estimate the relative reduction in the number of new infections attributed to each NPI. Among the NPIs considered, bans of large gatherings were most effective, followed by venue and school closures, whereas stay-at-home orders and work-from-home orders were least effective. With this retrospective cross-country analysis, we provide estimates regarding the effectiveness of different NPIs during the first epidemic wave. Public Library of Science 2021-06-02 /pmc/articles/PMC8171941/ /pubmed/34077448 http://dx.doi.org/10.1371/journal.pone.0252827 Text en © 2021 Banholzer et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Banholzer, Nicolas
van Weenen, Eva
Lison, Adrian
Cenedese, Alberto
Seeliger, Arne
Kratzwald, Bernhard
Tschernutter, Daniel
Salles, Joan Puig
Bottrighi, Pierluigi
Lehtinen, Sonja
Feuerriegel, Stefan
Vach, Werner
Estimating the effects of non-pharmaceutical interventions on the number of new infections with COVID-19 during the first epidemic wave
title Estimating the effects of non-pharmaceutical interventions on the number of new infections with COVID-19 during the first epidemic wave
title_full Estimating the effects of non-pharmaceutical interventions on the number of new infections with COVID-19 during the first epidemic wave
title_fullStr Estimating the effects of non-pharmaceutical interventions on the number of new infections with COVID-19 during the first epidemic wave
title_full_unstemmed Estimating the effects of non-pharmaceutical interventions on the number of new infections with COVID-19 during the first epidemic wave
title_short Estimating the effects of non-pharmaceutical interventions on the number of new infections with COVID-19 during the first epidemic wave
title_sort estimating the effects of non-pharmaceutical interventions on the number of new infections with covid-19 during the first epidemic wave
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8171941/
https://www.ncbi.nlm.nih.gov/pubmed/34077448
http://dx.doi.org/10.1371/journal.pone.0252827
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