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Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2

Huisman, Jana S. and Scire, Jérémie and Angst, Daniel C. and Li, Jinzhou and Neher, Richard A. and Maathuis, Marloes H. and Bonhoeffer, Sebastian and Stadler, Tanja. (2022) Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2. eLife, 11. p. 50.

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Abstract

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.
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology > Computational Modeling of Biological Processes (Neher)
UniBasel Contributors:Neher, Richard A
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:eLife Sciences Publications
e-ISSN:2050-084X
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
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Last Modified:06 Dec 2022 09:26
Deposited On:06 Dec 2022 09:26

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