strategies to reduce the risk of sars cov 2 importation from international travellers CORD-Papers-2022-06-02 (Version 1)

Title: Strategies to reduce the risk of SARS-CoV-2 importation from international travellers: modelling estimations for the United Kingdom July 2020
Abstract: BACKGROUND: To 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. AIM: To 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. METHODS: We 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. RESULTS: Quarantine 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): 8998) 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: 98100). 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: 8395)). CONCLUSION: The 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.
Published: 2021-09-30
Journal: Euro Surveill
DOI: 10.2807/1560-7917.es.2021.26.39.2001440
DOI_URL: http://doi.org/10.2807/1560-7917.es.2021.26.39.2001440
Author Name: Clifford Samuel
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Author Name: Quilty Billy J
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Author Name: Russell Timothy W
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Author Name: Liu Yang
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Author Name: Chan Yung Wai D
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Author Name: Pearson Carl A B
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Author Name: Knight Gwenan M
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Author Name: Procter Simon R
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Author Name: Simons David
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Author Name: Leclerc Quentin J
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Author Name: Munday James D
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Author Name: Gore Langton Georgia R
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Author Name: Jarvis Christopher I
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Author Name: Emery Jon C
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Author Name: Foss Anna M
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Author Name: O aposReilly Kathleen
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Author Name: Hellewell Joel
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Author Name: Nightingale Emily S
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Author Name: van Zandvoort Kevin
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Author Name: Tully Damien C
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Author Name: Abbott Sam
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Author Name: Abbas Kaja
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Author Name: Sun Fiona Yueqian
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sha: 8a4b8c0b979dc1a8e52138b9c0a55d68c429d650
license: cc-by
license_url: https://creativecommons.org/licenses/by/4.0/
source_x: Medline; PMC; WHO
source_x_url: https://www.medline.com/https://www.ncbi.nlm.nih.gov/pubmed/https://www.who.int/
pubmed_id: 34596018
pubmed_id_url: https://www.ncbi.nlm.nih.gov/pubmed/34596018
pmcid: PMC8485583
pmcid_url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8485583
url: https://doi.org/10.2807/1560-7917.es.2021.26.39.2001440 https://www.ncbi.nlm.nih.gov/pubmed/34596018/
has_full_text: TRUE
Keywords Extracted from Text Content: Figure S2 − Max GAM pre-infectious persons persons Wölfel travellers UK A. Kucirka P-splines Mod
Extracted Text Content in Record: First 5000 Characters:: Traveller movements in June 2019 and year on year change for May 2020 compared to May 2019 between UK airports, and airports in the European Union (EU) and United States of America (USA). Source: Civil Aviation Authority Tables 10.1 and 12.1 for July 2019 [1] , May 2019 [1] and May 2020 [2] . Total traveller volume July 2019 18,186,680 2,249,856 [1] Year-on-year change for April and May 2020 compared to April and May 2019, % -99% -99% [2] EU: Proportion asymptomatic derived from [4] We assume that the observed weekly travel volume, here, , is those who have not been screened out or self-selected out based on onset of symptoms, i.e. the sum of the number of uninfected, asymptomatic, and those ever-symptomatic travellers not currently symptomatic The total number of intending travellers, , is , plus those who do not travel, . We ' δ calculate as follows. First, sample . For , the proportion of ' ∼ ( = 7/30, ⌈ /2⌉) α infections which are asymptomatic, , the prevalence at the travel origin, , the proportion of π ξ ever-symptomatic cases who are symptomatic at intended time of departure, and , the ρ proportion of currently symptomatic travellers prevented from boarding, is distributed δ according to a negative binomial distribution with size and . is = 1 − π 1 − α ( )ρξ ξ estimated by sampling a large number of ever-symptomatic travellers, along with flight departure times and symptomatic periods and determining which proportion are symptomatic at time of intended departure. The number of uninfected travellers, , is then ; the number of ∼ (1 − π, + δ ) asymptomatic infected travellers is ; the number of travellers ∼ (α, + δ − ) At maximum stringency, the 14 day quarantine period aims to ensure that even a traveller who was infected just before or during the flight would likely spend their whole infectious period in quarantine and thereby not infect others. The moderately stringent strategy, on the other hand, aims to ensure that travellers spend a sufficient amount of time in quarantine to allow for the development of symptoms and probability of a positive PCR test leading to isolation for those infected. These strategies would, however, risk that some asymptomatically infected travellers (that is, infected travellers who will never display symptoms) will enter the community before the end of their infectious period. * In all scenarios we assumed that syndromic screening is implemented at the departure airport, hence low stringency rather than no stringency. The time-varying PCR sensitivity is modelled as a function of the time since an individual's exposure ( Figure 1 , Kucirka et al. 2020 [5] ) and derived by fitting a Generalised Additive Model (GAM) with a Binomial likelihood and penalised B-spline basis (P-spline) [6] , to the data collected by Kucirka et al. (2020) [5] . We shift the observations, as they have, by an incubation period of 5 days [7] , and augment by a pseudo-negative test on day 0 for each of the constituent data sets. [15] According to He et al. (2020) infectiousness of symptomatic cases begins up to 12.3 days (95%: (5.9, 17) days) prior to the onset of symptoms and peaks at onset of symptoms (0 days, 95%: -0.9, 0.9 days) [8, 16] . We sampled this pre-symptomatic infectious period duration to derive the time from exposure to infectiousness by matching the quantiles of the distribution of time to onset of symptoms to the quantiles of the distribution of infectiousness lead times for each traveller, preserving order, ensuring that no time to infectiousness occurs before exposure. The duration of the infectious period for symptomatic cases was derived from the data of Wölfel et al. (2020) [9] by fitting a Binomial GAM with P-splines to determine the probability of no longer being infectious as a function of days since onset of symptoms. The time to non-infectiousness is sampled from the fitted GAM, which has range (0,1), by the inverse transform method [17] . [5] The mean fit is used as the time-varying sensitivity function, , and hence no uncertainty is ( ) shown in the figure. B. Distributions of times to clinically relevant events, namely time from exposure to start and end, and duration, of symptoms for symptomatic infections (dark green), and infectiousness for both symptomatic and asymptomatic (light green) infections. Times greater than 30 days are collapsed to a single "30+" bin. As a baseline for comparison, we use the lowest stringency scenario considered: 70% of currently symptomatic travellers are prevented from boarding, but no quarantine or testing is conducted. In this scenario, between 2 and 12 (EU), and 3 and 24 (USA) infectious travellers would enter the community ( Figure S2A , low, no testing). By introducing a mandatory quarantine period of 7 days, this can be reduced to 0 to 3 infectious persons per week from the EU and 0 to 4 from the USA (Figure S2A, Mod.) , preventing approximately 80% of travellers from entering the community while being infectious (Rate Ratios, m
Keywords Extracted from PMC Text: UK quarantine-based 95–99 fly 88–97 1–14.2 0.00–0.04 45–56 Travellers taste Supplementary Table S3 US self-isolate Buitrago-Garcia 's pre-COVID-19 border Wolfel Quarantine Supplementary Table S1 Wuhan, 9–100 traveller throat COVID-19 post-arrival 24–92 pre-infectious travellers SARS-CoV-2 people SARS-CoV-2 RNA [9 beta nasopharyngeal coronavirus UK's National Health Service [22 [2,34]
Extracted PMC Text Content in Record: First 5000 Characters:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease (COVID-19), emerged in Wuhan, China in late 2019 and was rapidly disseminated globally through international air travel in the first half of 2020 [1]. In addition to non-pharmaceutical interventions (NPIs) to reduce domestic transmission, many countries implemented restrictions on incoming international travel such as mandatory quarantine, testing and travel bans, with the aim of preventing or reducing further importation and onward transmission [2]. During this early period of the COVID-19 pandemic prior to the roll-out of vaccines in late 2020, a number of countries in Europe and the Asia Pacific region implemented a mandatory quarantine upon arrival, which typically had a duration of 14 days [2,3]. It is expected that, by day 14, at least 95% of all infected individuals who will become symptomatic have done so [4]. However, the median incubation period for SARS-CoV-2 is ca 5 days (95% confidence interval: 4.1 to 7.0) [4] and, assuming that travellers are equally likely to travel at any point in this period, a 5-day quarantine on arrival should suffice to allow more than 50% of the infected travellers to become symptomatic and be managed accordingly. Quarantine, either at home or at managed facilities [5], may lead to negative psychological effects stemming from social isolation [6,7] and financial stress [8]. Hence, there is considerable interest in reducing the period of quarantine, assuming it is safe to do so. In addition to quarantine, several countries introduced a requirement for travellers to undergo testing for SARS-CoV-2 infection with RT-PCR (hereafter PCR). Such testing is commonly performed by taking nasopharyngeal or throat swabs of individuals and analysing the resulting sample for the presence of SARS-CoV-2 RNA [9]. PCR screening may be conducted before the flight and/or after arrival to allow detection of infected travellers. In some countries, testing is also used to reduce or eliminate quarantine for travellers without a confirmed infection. For example, in the summer of 2020, Japan allowed business travellers from designated low-risk countries to bypass the 14-day quarantine period given a negative PCR test result upon arrival [10]. Here we investigated the effectiveness of several strategies available in the pre-vaccination era of the SARS-CoV-2 pandemic to reduce the number of arriving infectious travellers as well as the potential for transmission in the community. We assessed the impact of varying the duration of quarantine and the timing and number of PCR tests, as well as the prevalence in and travel volume from the European Union (EU) and the United States (US) to the United Kingdom (UK) as of July 2020, while also accounting for the natural history of SARS-CoV-2 infection. The possible SARS-CoV-2 screening outcomes for air travellers are as follows: (i) prevented from travelling following detection of SARS-CoV-2 infection either through syndromic screening at the airport or a positive pre-flight PCR test, (ii) released after the mandatory isolation period following detection of SARS-CoV-2 infection either by a positive PCR test upon entry or a follow-up positive PCR test after a negative result upon entry, (iii) released after a second negative test during the quarantine period, and (iv) in the absence of post-entry testing, travellers will be released after the mandatory quarantine period (which, in the model, may have a duration of 0 days) (Figure 1). We simulated the number of infected air travellers intending to fly to a destination country in a given week based on the monthly volume of flights between the origin and destination, and considering the prevalence of COVID-19 in the origin country (Supplementary Table S1). We used the UK as a case study for the destination country. We assumed that the inbound and outbound travel is balanced on average. To estimate the number of people travelling into the UK, we halved the total number of monthly traveller movements. The time of each intending traveller's flight was sampled uniformly between the time of exposure to SARS-CoV-2 and time of recovery. We modelled international travellers coming either from the US or the EU, using publicly available Civil Aviation Authority data for April and May 2020 [11,12]. Estimates of current COVID-19 infection prevalence were derived from reported cases and death time series data while adjusting for reporting delays and under-reporting based on case-fatality ratio estimates [13,14]. EU-wide prevalence was calculated as a population-weighted mean of available country-level estimates of the non-UK EU countries (except Malta, for which a prevalence estimate was not available). For each simulation, we sampled the number of weekly intending travellers, the proportion of those who were infected, and the proportion of infected travellers who were symptomatic and asymptomatic [15] (details are pro
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