Estimating the burden of SARS-CoV-2 in France.


Journal

Science (New York, N.Y.)
ISSN: 1095-9203
Titre abrégé: Science
Pays: United States
ID NLM: 0404511

Informations de publication

Date de publication:
10 07 2020
Historique:
received: 20 04 2020
accepted: 11 05 2020
pubmed: 15 5 2020
medline: 17 7 2020
entrez: 15 5 2020
Statut: ppublish

Résumé

France has been heavily affected by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic and went into lockdown on 17 March 2020. Using models applied to hospital and death data, we estimate the impact of the lockdown and current population immunity. We find that 2.9% of infected individuals are hospitalized and 0.5% of those infected die (95% credible interval: 0.3 to 0.9%), ranging from 0.001% in those under 20 years of age to 8.3% in those 80 years of age or older. Across all ages, men are more likely to be hospitalized, enter intensive care, and die than women. The lockdown reduced the reproductive number from 2.90 to 0.67 (77% reduction). By 11 May 2020, when interventions are scheduled to be eased, we project that 3.5 million people (range: 2.1 million to 6.0 million), or 5.3% of the population (range: 3.3 to 9.3%), will have been infected. Population immunity appears to be insufficient to avoid a second wave if all control measures are released at the end of the lockdown.

Identifiants

pubmed: 32404476
pii: science.abc3517
doi: 10.1126/science.abc3517
pmc: PMC7223792
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

208-211

Commentaires et corrections

Type : ErratumIn

Informations de copyright

Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

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Auteurs

Henrik Salje (H)

Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.
Department of Genetics, University of Cambridge, Cambridge, UK.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

Cécile Tran Kiem (C)

Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.
Collège Doctoral, Sorbonne Université, Paris, France.

Noémie Lefrancq (N)

Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.

Noémie Courtejoie (N)

DREES, Ministère des Solidarités et de la Santé, Paris, France.

Paolo Bosetti (P)

Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.

Juliette Paireau (J)

Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.
Santé Publique France, French National Public Health Agency, Saint-Maurice, France.

Alessio Andronico (A)

Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.

Nathanaël Hozé (N)

Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.

Jehanne Richet (J)

DREES, Ministère des Solidarités et de la Santé, Paris, France.

Claire-Lise Dubost (CL)

DREES, Ministère des Solidarités et de la Santé, Paris, France.

Yann Le Strat (Y)

Santé Publique France, French National Public Health Agency, Saint-Maurice, France.

Justin Lessler (J)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

Daniel Levy-Bruhl (D)

Santé Publique France, French National Public Health Agency, Saint-Maurice, France.

Arnaud Fontanet (A)

Emerging Diseases Epidemiology Unit, Institut Pasteur, Paris, France.
PACRI Unit, Conservatoire National des Arts et Métiers, Paris, France.

Lulla Opatowski (L)

Epidemiology and Modelling of Antibiotic Evasion Unit, Institut Pasteur, Paris, France.
Anti-infective Evasion and Pharmacoepidemiology Team, CESP, Université Paris-Saclay, UVSQ, INSERM U1018, Montigny-le-Bretonneux, France.

Pierre-Yves Boelle (PY)

Institut Pierre Louis d'Epidémiologie et de Santé Publique, Sorbonne Université, INSERM, Paris, France.

Simon Cauchemez (S)

Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France. simon.cauchemez@pasteur.fr.

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Classifications MeSH