About: Bayesian investigation of SARS-CoV-2-related mortality in France

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About: Bayesian investigation of SARS-CoV-2-related mortality in France Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Bayesian investigation of SARS-CoV-2-related mortality in France
Creator	Boussau, Bastien Duchemin, Louis Veber, Philippe
Source	MedRxiv
abstract	The SARS-CoV-2 epidemic in France has focused a lot of attention as it has had one of the largest death tolls in Europe. It provides an opportunity to examine the effect of the lockdown and of other events on the dynamics of the epidemic. In particular, it has been suggested that municipal elections held just before lockdown was ordered may have helped spread the virus. In this manuscript we use a Bayesian model of the number of deaths through time to study the epidemic in 13 regions of France. We found that the model accurately predicts the number of deaths 2 to 3 weeks in advance, and recovers estimates that are in agreement with recent models that rely on a different structure and different input data. We found that the lockdown had a similar effect on the reproduction rate in all 13 regions, decreasing it by 80 %. Our model predicts that 2.09 (95% CI : 1.69-2.66) million people had been infected by May 11, and that there were 2793 (95% CI : 1761-4543) new infections on May 11. We found no evidence that the reproduction rates differ between week-ends and week days, and no evidence that the reproduction rates increased on the election day. Finally, we evaluated counterfactual scenarios showing that ordering the lockdown 1 to 7 days sooner would have resulted in 18% to 85% fewer deaths, but that ordering it 1 to 7 days later would have resulted in 21% to 262% more deaths. Overall, the predictions of the model indicate that holding the elections on March 15 did not have a detectable impact on the total number of deaths, unless it motivated a delay in imposing the lockdown.
has issue date	2020-06-11(xsd:dateTime)
bibo:doi	10.1101/2020.06.09.20126862
has license	medrxiv
sha1sum (hex)	016ae4cd21a22d45d9595f4c54df7a7f570aec26
schema:url	https://doi.org/10.1101/2020.06.09.20126862
resource representing a document's title	Bayesian investigation of SARS-CoV-2-related mortality in France
resource representing a document's body	covid:016ae4cd21a22d45d9595f4c54df7a7f570aec26#body_text
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