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Estimating the Risk of Outbreaks of COVID-19 Associated with Shore Leave by Merchant Ship Crews: Simulation Studies for a Case Country (preprint)
medrxiv; 2020.
Preprint Dans Anglais | medRxiv | ID: ppzbmed-10.1101.2020.09.08.20190769
ABSTRACT

Aim:

We aimed to estimate the risk of COVID-19 outbreaks in a case study COVID-free destination country, associated with shore leave for merchant ship crews.

Methods:

A stochastic version of the SEIR model CovidSIM v1.1, designed specifically for COVID-19 was utilised. It was populated with parameters for SARS-CoV-2 transmission, shipping characteristics, and plausible control measures.

Results:

When no control interventions were in place, an outbreak of COVID-19 in our case study destination country (New Zealand; NZ) was estimated to occur after a median time of 23 days (assuming a global average for source country incidence of 2.66 new infections per 1000 population per week, a crew of 20, a voyage length of 10 days, 1 day of shore leave both in NZ and abroad, and 108 port visits by international merchant ships per week). For this example the uncertainty around when outbreaks occur is wide (an outbreak occurs with 95% probability between 1 and 124 days). The combined use of a PCR test on arrival, self-reporting of symptoms with contact tracing, and mask use during shore leave, increased this median time to 1.0 year (14 days to 5.4 years). Scenario analyses found that onboard infection chains could persist for well over 4 weeks even with crews of only 5 members.

Conclusion:

Introduction of SARS-CoV-2 through shore leave from international shipping crews is likely, even after long voyages. The risk can be substantially mitigated by control measures such as PCR testing and mask use.
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Texte intégral: Disponible Collection: Preprints Base de données: medRxiv Sujet Principal: COVID-19 / Infections langue: Anglais Année: 2020 Type de document: Preprint

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Texte intégral: Disponible Collection: Preprints Base de données: medRxiv Sujet Principal: COVID-19 / Infections langue: Anglais Année: 2020 Type de document: Preprint