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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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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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. |
format | Online Article Text |
id | pubmed-8171941 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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