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Clifford S, Quilty BJ, Russell TW, Liu Y, Chan YWD, Pearson CAB, Eggo RM, Endo A, Flasche S, Edmunds WJ. Strategies to reduce the risk of SARS-CoV-2 importation from international travellers: modelling estimations for the United Kingdom, July 2020. Euro Surveill 2021; 26:2001440. [PMID: 34596018 PMCID: PMC8485583 DOI: 10.2807/1560-7917.es.2021.26.39.2001440] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Accepted: 02/16/2021] [Indexed: 12/23/2022] Open
Abstract
BackgroundTo mitigate SARS-CoV-2 transmission risks from international air travellers, many countries implemented a combination of up to 14 days of self-quarantine upon arrival plus PCR testing in the early stages of the COVID-19 pandemic in 2020.AimTo assess the effectiveness of quarantine and testing of international travellers to reduce risk of onward SARS-CoV-2 transmission into a destination country in the pre-COVID-19 vaccination era.MethodsWe used a simulation model of air travellers arriving in the United Kingdom from the European Union or the United States, incorporating timing of infection stages while varying quarantine duration and timing and number of PCR tests.ResultsQuarantine upon arrival with a PCR test on day 7 plus a 1-day delay for results can reduce the number of infectious arriving travellers released into the community by a median 94% (95% uncertainty interval (UI): 89-98) compared with a no quarantine/no test scenario. This reduction is similar to that achieved by a 14-day quarantine period (median > 99%; 95% UI: 98-100). Even shorter quarantine periods can prevent a substantial amount of transmission; all strategies in which travellers spend at least 5 days (mean incubation period) in quarantine and have at least one negative test before release are highly effective (median reduction 89%; 95% UI: 83-95)).ConclusionThe effect of different screening strategies impacts asymptomatic and symptomatic individuals differently. The choice of an optimal quarantine and testing strategy for unvaccinated air travellers may vary based on the number of possible imported infections relative to domestic incidence.
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Affiliation(s)
- Samuel Clifford
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Billy J Quilty
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Timothy W Russell
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Yang Liu
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Yung-Wai D Chan
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Carl A B Pearson
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Rosalind M Eggo
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Akira Endo
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Stefan Flasche
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - W John Edmunds
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
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