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Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2
The effective reproductive number R(e) is a key indicator of the growth of an epidemic. Since the start of the SARS-CoV-2 pandemic, many methods and online dashboards have sprung up to monitor this number through time. However, these methods are not always thoroughly tested, correctly placed in time...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9467515/ https://www.ncbi.nlm.nih.gov/pubmed/35938911 http://dx.doi.org/10.7554/eLife.71345 |
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author | Huisman, Jana S Scire, Jérémie Angst, Daniel C Li, Jinzhou Neher, Richard A Maathuis, Marloes H Bonhoeffer, Sebastian Stadler, Tanja |
author_facet | Huisman, Jana S Scire, Jérémie Angst, Daniel C Li, Jinzhou Neher, Richard A Maathuis, Marloes H Bonhoeffer, Sebastian Stadler, Tanja |
author_sort | Huisman, Jana S |
collection | PubMed |
description | The effective reproductive number R(e) is a key indicator of the growth of an epidemic. Since the start of the SARS-CoV-2 pandemic, many methods and online dashboards have sprung up to monitor this number through time. However, these methods are not always thoroughly tested, correctly placed in time, or are overly confident during high incidence periods. Here, we present a method for timely estimation of R(e), applied to COVID-19 epidemic data from 170 countries. We thoroughly evaluate the method on simulated data, and present an intuitive web interface for interactive data exploration. We show that, in early 2020, in the majority of countries the estimated R(e) dropped below 1 only after the introduction of major non-pharmaceutical interventions. For Europe the implementation of non-pharmaceutical interventions was broadly associated with reductions in the estimated R(e). Globally though, relaxing non-pharmaceutical interventions had more varied effects on subsequent R(e) estimates. Our framework is useful to inform governments and the general public on the status of epidemics in their country, and is used as the official source of R(e) estimates for SARS-CoV-2 in Switzerland. It further allows detailed comparison between countries and in relation to covariates such as implemented public health policies, mobility, behaviour, or weather data. |
format | Online Article Text |
id | pubmed-9467515 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-94675152022-09-13 Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2 Huisman, Jana S Scire, Jérémie Angst, Daniel C Li, Jinzhou Neher, Richard A Maathuis, Marloes H Bonhoeffer, Sebastian Stadler, Tanja eLife Epidemiology and Global Health The effective reproductive number R(e) is a key indicator of the growth of an epidemic. Since the start of the SARS-CoV-2 pandemic, many methods and online dashboards have sprung up to monitor this number through time. However, these methods are not always thoroughly tested, correctly placed in time, or are overly confident during high incidence periods. Here, we present a method for timely estimation of R(e), applied to COVID-19 epidemic data from 170 countries. We thoroughly evaluate the method on simulated data, and present an intuitive web interface for interactive data exploration. We show that, in early 2020, in the majority of countries the estimated R(e) dropped below 1 only after the introduction of major non-pharmaceutical interventions. For Europe the implementation of non-pharmaceutical interventions was broadly associated with reductions in the estimated R(e). Globally though, relaxing non-pharmaceutical interventions had more varied effects on subsequent R(e) estimates. Our framework is useful to inform governments and the general public on the status of epidemics in their country, and is used as the official source of R(e) estimates for SARS-CoV-2 in Switzerland. It further allows detailed comparison between countries and in relation to covariates such as implemented public health policies, mobility, behaviour, or weather data. eLife Sciences Publications, Ltd 2022-08-08 /pmc/articles/PMC9467515/ /pubmed/35938911 http://dx.doi.org/10.7554/eLife.71345 Text en © 2022, Huisman, Scire et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Epidemiology and Global Health Huisman, Jana S Scire, Jérémie Angst, Daniel C Li, Jinzhou Neher, Richard A Maathuis, Marloes H Bonhoeffer, Sebastian Stadler, Tanja Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2 |
title | Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2 |
title_full | Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2 |
title_fullStr | Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2 |
title_full_unstemmed | Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2 |
title_short | Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2 |
title_sort | estimation and worldwide monitoring of the effective reproductive number of sars-cov-2 |
topic | Epidemiology and Global Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9467515/ https://www.ncbi.nlm.nih.gov/pubmed/35938911 http://dx.doi.org/10.7554/eLife.71345 |
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