Effectiveness of interventions targeting air travellers for delaying local outbreaks of SARS-CoV-2.


Journal

Journal of travel medicine
ISSN: 1708-8305
Titre abrégé: J Travel Med
Pays: England
ID NLM: 9434456

Informations de publication

Date de publication:
20 08 2020
Historique:
received: 28 02 2020
revised: 20 04 2020
accepted: 04 05 2020
pubmed: 10 5 2020
medline: 4 9 2020
entrez: 9 5 2020
Statut: ppublish

Résumé

We evaluated if interventions aimed at air travellers can delay local severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) community transmission in a previously unaffected country. We simulated infected air travellers arriving into countries with no sustained SARS-CoV-2 transmission or other introduction routes from affected regions. We assessed the effectiveness of syndromic screening at departure and/or arrival and traveller sensitisation to the COVID-2019-like symptoms with the aim to trigger rapid self-isolation and reporting on symptom onset to enable contact tracing. We assumed that syndromic screening would reduce the number of infected arrivals and that traveller sensitisation reduces the average number of secondary cases. We use stochastic simulations to account for uncertainty in both arrival and secondary infections rates, and present sensitivity analyses on arrival rates of infected travellers and the effectiveness of traveller sensitisation. We report the median expected delay achievable in each scenario and an inner 50% interval. Under baseline assumptions, introducing exit and entry screening in combination with traveller sensitisation can delay a local SARS-CoV-2 outbreak by 8 days (50% interval: 3-14 days) when the rate of importation is 1 infected traveller per week at time of introduction. The additional benefit of entry screening is small if exit screening is effective: the combination of only exit screening and traveller sensitisation can delay an outbreak by 7 days (50% interval: 2-13 days). In the absence of screening, with less effective sensitisation, or a higher rate of importation, these delays shrink rapidly to <4 days. Syndromic screening and traveller sensitisation in combination may have marginally delayed SARS-CoV-2 outbreaks in unaffected countries.

Sections du résumé

BACKGROUND
We evaluated if interventions aimed at air travellers can delay local severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) community transmission in a previously unaffected country.
METHODS
We simulated infected air travellers arriving into countries with no sustained SARS-CoV-2 transmission or other introduction routes from affected regions. We assessed the effectiveness of syndromic screening at departure and/or arrival and traveller sensitisation to the COVID-2019-like symptoms with the aim to trigger rapid self-isolation and reporting on symptom onset to enable contact tracing. We assumed that syndromic screening would reduce the number of infected arrivals and that traveller sensitisation reduces the average number of secondary cases. We use stochastic simulations to account for uncertainty in both arrival and secondary infections rates, and present sensitivity analyses on arrival rates of infected travellers and the effectiveness of traveller sensitisation. We report the median expected delay achievable in each scenario and an inner 50% interval.
RESULTS
Under baseline assumptions, introducing exit and entry screening in combination with traveller sensitisation can delay a local SARS-CoV-2 outbreak by 8 days (50% interval: 3-14 days) when the rate of importation is 1 infected traveller per week at time of introduction. The additional benefit of entry screening is small if exit screening is effective: the combination of only exit screening and traveller sensitisation can delay an outbreak by 7 days (50% interval: 2-13 days). In the absence of screening, with less effective sensitisation, or a higher rate of importation, these delays shrink rapidly to <4 days.
CONCLUSION
Syndromic screening and traveller sensitisation in combination may have marginally delayed SARS-CoV-2 outbreaks in unaffected countries.

Identifiants

pubmed: 32384159
pii: 5834629
doi: 10.1093/jtm/taaa068
pmc: PMC7239177
pii:
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 208812/Z/17/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 210758/Z/18/Z
Pays : United Kingdom

Informations de copyright

© International Society of Travel Medicine 2020.

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Auteurs

Samuel Clifford (S)

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK.

Carl A B Pearson (CAB)

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK.
South African DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), University of Stellenbosch, 19 Jonkershoek Road, Stellenbosch, 7600, South Africa.

Petra Klepac (P)

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK.

Kevin Van Zandvoort (K)

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK.

Billy J Quilty (BJ)

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK.

Rosalind M Eggo (RM)

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK.

Stefan Flasche (S)

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK.

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