Effectiveness of airport screening at detecting travellers infected with novel coronavirus (2019-nCoV).


Journal

Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin
ISSN: 1560-7917
Titre abrégé: Euro Surveill
Pays: Sweden
ID NLM: 100887452

Informations de publication

Date de publication:
02 2020
Historique:
entrez: 13 2 2020
pubmed: 13 2 2020
medline: 19 3 2020
Statut: ppublish

Résumé

We evaluated effectiveness of thermal passenger screening for 2019-nCoV infection at airport exit and entry to inform public health decision-making. In our baseline scenario, we estimated that 46% (95% confidence interval: 36 to 58) of infected travellers would not be detected, depending on incubation period, sensitivity of exit and entry screening, and proportion of asymptomatic cases. Airport screening is unlikely to detect a sufficient proportion of 2019-nCoV infected travellers to avoid entry of infected travellers.

Identifiants

pubmed: 32046816
doi: 10.2807/1560-7917.ES.2020.25.5.2000080
pmc: PMC7014668
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/S003975/1
Pays : United Kingdom

Commentaires et corrections

Type : ErratumIn

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Auteurs

Billy J Quilty (BJ)

Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.

Sam Clifford (S)

Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
The members of the Centre for the Mathematical Modelling of Infectious Diseases (CMMID) nCoV working group are listed at the end of the article.
These authors contributed equally to this work.

Stefan Flasche (S)

Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
These authors contributed equally to this work.

Rosalind M Eggo (RM)

Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
These authors contributed equally to this work.

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Classifications MeSH