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PMC:7014668 JSONTXT 23 Projects

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Id Subject Object Predicate Lexical cue
T1 0-102 Sentence denotes Effectiveness of airport screening at detecting travellers infected with novel coronavirus (2019-nCoV)
T2 104-112 Sentence denotes Abstract
T3 113-261 Sentence denotes We evaluated effectiveness of thermal passenger screening for 2019-nCoV infection at airport exit and entry to inform public health decision-making.
T4 262-335 Sentence denotes In our baseline scenario, we estimated that 46% (95% confidence interval:
T5 336-502 Sentence denotes 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.
T6 503-638 Sentence denotes Airport screening is unlikely to detect a sufficient proportion of 2019-nCoV infected travellers to avoid entry of infected travellers.
T7 640-786 Sentence denotes As at 4 February 2020, 20,471 confirmed cases of novel coronavirus (2019-nCoV) have been reported from China with 425 deaths confirmed so far [1].
T8 787-918 Sentence denotes There were cases in at least 23 other countries, identified because of symptoms and recent travel history to Hubei province, China.
T9 919-1057 Sentence denotes This strongly suggests that the reported cases constitute only a small fraction of the actual number of infected individuals in China [2].
T10 1058-1237 Sentence denotes While the most affected region, Hubei province, has ceased air travel and closed major public transport routes [3] the number of exported cases are still expected to increase [4].
T11 1238-1487 Sentence denotes Despite limited evidence for its effectiveness, airport screening has been previously implemented during the 2003 SARS epidemic and 2009 influenza A(H1N1) pandemic to limit the probability of infected cases entering other countries or regions [5-7].
T12 1488-1747 Sentence denotes Here we use the available evidence on the incubation time, hospitalisation time and proportion of asymptomatic infections of 2019-nCoV to evaluate the effectiveness of exit and entry screening for detecting travellers entering Europe with 2019-nCoV infection.
T13 1748-1847 Sentence denotes We also present an online tool so that results can be updated as new information becomes available.
T14 1849-1915 Sentence denotes Simulation of travellers at each stage of infection with 2019-nCoV
T15 1916-2053 Sentence denotes We simulated 100 2019-nCoV infected travellers planning to board a flight who would pose a risk for seeding transmission in a new region.
T16 2054-2192 Sentence denotes The duration of travel was considered as the flight time plus a small amount of additional travel time (ca 1 hour) for airport procedures.
T17 2193-2434 Sentence denotes We assumed that infected individuals will develop symptoms, including fever, at the end of their incubation period (mean 5.2 days (Table)) [8] and progress to more severe symptoms after a few days, resulting in hospitalisation and isolation.
T18 2435-2798 Sentence denotes We also took into account that individuals may have asymptomatic (subclinical) infection that would not be detected by thermal scanning or cause them to seek medical care, although these individuals may be infectious, and that infected travellers may exhibit severe symptoms during their travel and be hospitalised upon arrival without undergoing entry screening.
T19 2799-3210 Sentence denotes We then estimated the proportion of infected travellers who would be detected by exit and entry screening, develop severe symptoms during travel, or go undetected, under varying assumptions of: (i) the duration of travel; (ii) the sensitivity of exit and entry screening; (iii) the proportion of asymptomatic infections; (iv) the incubation period and (v) the time from symptom onset to hospitalisation (Table).
T20 3211-3410 Sentence denotes Table Parameter values and assumptions for the baseline scenario estimating effectiveness of exit and entry screening at airports for detecting passengers infected with novel coronavirus (2019-nCoV)
T21 3411-3455 Sentence denotes Parameter Value (baseline scenario) Source
T22 3456-3507 Sentence denotes Duration of travel 12 hours Beijing – London [18]
T23 3508-3595 Sentence denotes Sensitivity of exit screening 86% Sensitivity of infrared thermal image scanners [19]
T24 3596-3684 Sentence denotes Sensitivity of entry screening 86% Sensitivity of infrared thermal image scanners [19]
T25 3685-3837 Sentence denotes Proportion of asymptomatic infections undetectable by typical screening procedures 17% 1 of 6 reported asymptomatic in a 2019-nCoV family cluster [11]
T26 3838-3980 Sentence denotes Incubation period Mean 5.2 days, variance 4.1 days Reported Gamma distributed mean, variance estimated from uncertainty interval of mean [8]
T27 3981-4389 Sentence denotes Time from symptom onset to hospitalisation Mean 9.1 days, variance 14.7 days Reported Gamma distributed mean, variance estimated from uncertainty interval of mean [8] We assume that the time of starting travel is randomly and uniformly distributed between the time of infection and twice the expected time to severe disease, ensuring that simulated travellers are travelling during their incubation period.
T28 4390-4536 Sentence denotes However, we only consider those travellers who depart before their symptoms progress to being so severe that they would require hospital care [8].
T29 4537-4751 Sentence denotes We simulate travellers with individual incubation period, time from onset to severe disease, flight start times and detection success at exit and entry screening according to the screening sensitivities (Figure 1).
T30 4752-4980 Sentence denotes An individual will be detected at exit screening if their infection is symptomatic i.e. has detectable fever, their departure time exceeds their incubation period, and their stochastic exit screening success indicates detection.
T31 4981-5265 Sentence denotes An individual will be detected at entry screening if their infection is symptomatic, their incubation period ends after their departure but before their arrival, they have not been detected at exit screening, and their entry screening result is positive despite imperfect sensitivity.
T32 5266-5421 Sentence denotes Entry screening detections are further divided into detection due to severe symptoms and detection of mild symptoms via equipment such as thermal scanners.
T33 5422-5498 Sentence denotes We used 10,000 bootstrap samples to calculate 95% confidence intervals (CI).
T34 5499-5596 Sentence denotes Figure 1 Simulated infection histories of travellers infected with novel coronavirus (2019-nCoV)
T35 5597-5716 Sentence denotes The incubation period begins on infection and travellers then progress to being symptomatic and having severe symptoms.
T36 5717-5878 Sentence denotes Travellers may fly at any point within the incubation or symptomatic phases; any would-be travellers who show (severe) symptoms and are hospitalised before exit.
T37 5879-6011 Sentence denotes Vertical lines represent the exit screening at start of travel (solid) and entry screening at end of travel (dashed) 12 hours later.
T38 6012-6183 Sentence denotes The model code is available via GitHub [9] and the results can be further explored in a Shiny app [10] at https://cmmid-lshtm.shinyapps.io/traveller_screening/ (Figure 2).
T39 6184-6476 Sentence denotes Figure 2 Screenshot of Shiny appa displaying the number of travellers infected with novel coronavirus (2019-nCoV) detected at airport exit and entry screening with baseline assumptionsb, 95% bootstrap confidence intervals, time distributions for incubation period and time to severe disease*
T40 6477-6490 Sentence denotes a Source [9].
T41 6491-6537 Sentence denotes b Baseline assumptions according to the Table.
T42 6538-6697 Sentence denotes Results are from stochastic simulation, and so there may be small variations in the number of travellers in each group when the same parameters are used twice.
T43 6698-6884 Sentence denotes Sliders are provided to modify the duration of travel, the sensitivity of both exit and entry screening, the proportion symptomatic, and the natural history parameters for the infection.
T44 6886-6918 Sentence denotes Effect of screening on detection
T45 6919-6974 Sentence denotes For the baseline scenario we estimated that 44 (95% CI:
T46 6975-7062 Sentence denotes 33–56) of 100 infected travellers would be detected by exit screening, no case (95% CI:
T47 7063-7126 Sentence denotes 0–3) would develop severe symptoms during travel, nine (95% CI:
T48 7127-7217 Sentence denotes 2–16) additional cases would be detected by entry screening, and the remaining 46 (95% CI:
T49 7218-7247 Sentence denotes 36–58) would not be detected.
T50 7248-7358 Sentence denotes The effectiveness of entry screening is largely dependent on the effectiveness of the exit screening in place.
T51 7359-7427 Sentence denotes Under baseline assumptions, entry screening could detect 53 (95% CI:
T52 7428-7505 Sentence denotes 35–72) instead of nine infected travellers if no exit screening was in place.
T53 7506-7672 Sentence denotes However, the probability of developing symptoms during the flight increases with flight time and hence exit screening is more effective for longer flights (Figure 3).
T54 7673-7842 Sentence denotes Figure 3 Probability of detecting travellers infected with novel coronavirus (2019-nCoV) at airport entry screening by travel duration and sensitivity of exit screening
T55 7843-7891 Sentence denotes Each cell is a mean of 10,000 model simulations.
T56 7892-8056 Sentence denotes Other parameters (incubation period, symptom onset to hospitalisation period, and proportion of asymptomatic infections) were fixed at baseline assumptions (Table).
T57 8057-8149 Sentence denotes Intervals are probabilities of detection, binned at increments of 10% (0–10%, 10–20%, etc.).
T58 8150-8356 Sentence denotes Syndromic screening designed to prevent infected and potentially infectious cases entering a country undetected is highly vulnerable to the proportion of asymptomatic infections and long incubation periods.
T59 8357-8747 Sentence denotes If our baseline scenario is modified to have 0% asymptomatic 2019-nCoV infections and 100% sensitivity of entry screening, the incubation period will need to be around 10-fold shorter than the period from symptom onset to severe disease (e.g. hospitalisation) in order to detect more than 90% of infected travellers that would not otherwise report illness at either exit or entry screening.
T60 8749-8775 Sentence denotes Discussion and conclusions
T61 8776-8946 Sentence denotes As a response to the ongoing outbreak of the 2019-nCoV originating in Wuhan, exit screening has been implemented for international flights leaving China’s major airports.
T62 8947-9144 Sentence denotes Thermal scanning, which can identify passengers with fever (high external body temperature), allows for passengers exhibiting symptoms of 2019-nCoV infection to be tested before they board a plane.
T63 9145-9296 Sentence denotes Similarly, entry screening for flights originating in the most affected regions may be under consideration at airports in regions in and outside China.
T64 9297-9643 Sentence denotes We estimate that the key goal of syndromic screening at airports - to prevent infected travellers from entering countries or regions with little or no ongoing transmission - is only achievable if the rate of asymptomatic infections that are transmissible is negligible, screening sensitivity is almost perfect, and the incubation period is short.
T65 9644-9835 Sentence denotes Based on early data from Li et al. [8], 2019-nCoV appears to have a shorter incubation period than severe acute respiratory syndrome (SARS), and a higher rate of asymptomatic infections [11].
T66 9836-9958 Sentence denotes Under generally conservative assumptions on sensitivity, we find that 46 of 100 infected travellers will enter undetected.
T67 9959-10066 Sentence denotes Entry screening is an intuitive barrier for the prevention of infected people entering a country or region.
T68 10067-10251 Sentence denotes However, evidence on its effectiveness remains limited and given its lack of specificity, it generates a high overhead of screened travellers uninfected with the targeted pathogen [5].
T69 10252-10444 Sentence denotes For example, when entry screening was implemented in Australia in response to the 2003 SARS outbreak, 1.84 million people were screened, 794 were quarantined, and no cases were confirmed [12].
T70 10445-10653 Sentence denotes While some cases of 2019-nCoV infection have been identified through airport screening in the current outbreak, our estimates indicate that likely more infected travellers have not been detected by screening.
T71 10654-10823 Sentence denotes It is important to note that our estimates are based on a number of key assumptions that cannot yet be informed directly by evidence from the ongoing 2019-nCoV outbreak.
T72 10824-10953 Sentence denotes The current outbreak has spread rapidly and early evidence suggests that the average disease severity is lower than that of SARS.
T73 10954-11023 Sentence denotes This may also suggest a substantial proportion of asymptomatic cases.
T74 11024-11228 Sentence denotes A recent analysis of a family transmission cluster is based on a small sample size but one in six infections was asymptomatic [11]; this is a major impediment for the effectiveness of syndromic screening.
T75 11229-11347 Sentence denotes However, if asymptomatic cases were not infectious they would not pose a risk for seeding infection chains on arrival.
T76 11348-11554 Sentence denotes To allow easy adaptation of our results as new insight becomes available in the coming weeks, we developed a free interactive online tool, available at https://cmmid-lshtm.shinyapps.io/traveller_screening/.
T77 11555-11771 Sentence denotes While the most up-to-date data on the incubation period or the time until recovery from 2019-nCoV infection have been used in this analysis, these figures are likely to change over time as more data become available.
T78 11772-12035 Sentence denotes Unless the incubation period is only a small fraction of the duration of infection in relation to that of symptomatic disease, and fever in particular, syndromic screening is likely to detect an insufficient fraction of infected cases to prevent local infections.
T79 12036-12140 Sentence denotes In addition, the sensitivity of airport screening for the detection of 2019-nCoV has not been evaluated.
T80 12141-12285 Sentence denotes However, we chose conservative estimates and show that with reduced sensitivity, the effectiveness of syndromic screening would further decline.
T81 12286-12451 Sentence denotes In many international airports, information is provided to travellers from affected regions recommending action if they develop symptoms on or after arrival [13-16].
T82 12452-12606 Sentence denotes Some countries, for example Japan, also require incoming passengers to complete forms detailing their past and future travel in order to aid tracing [17].
T83 12607-12903 Sentence denotes Due to the duration of the incubation period of 2019-nCoV infection, we find that exit or entry screening at airports for initial symptoms, via thermal scanners or similar, is unlikely to prevent passage of infected travellers into new countries or regions where they may seed local transmission.
T84 12905-12921 Sentence denotes Acknowledgements
T85 12922-13065 Sentence denotes SF and SC are supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant number 208812/Z/17/Z).
T86 13066-13143 Sentence denotes RME acknowledges an HDR UK Innovation Fellowship (Grant number MR/S003975/1).
T87 13144-13295 Sentence denotes BJQ was funded by the National Institute for Health Research (NIHR) (16/137/109) using UK aid from the UK Government to support global health research.
T88 13296-13457 Sentence denotes The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the UK Department of Health and Social Care.
T89 13458-13502 Sentence denotes CMMID nCoV working group funding statements:
T90 13503-14074 Sentence denotes Yang Liu (Gates (INV-003174), NIHR (16/137/109)), Charlie Diamond (NIHR (16/137/109)), Sebastian Funk (Wellcome Trust (210758/Z/18/Z)), Amy Gimma (Global Challenges Research Fund (GCRF) for the project "RECAP" managed through RCUK and ESRC (ES/P010873/1)), James D Munday (Wellcome Trust (210758/Z/18/Z)), Hamish Gibbs (NIHR (ITCRZ 03010)), Sam Abbott (Wellcome Trust (210758/Z/18/Z)), Timothy W Russell (Wellcome Trust (206250/Z/17/Z)), Petra Klepac (Gates (INV-003174)), Mark Jit (Gates (INV-003174), NIHR (16/137/109)), Joel Hellewell (Wellcome Trust (210758/Z/18/Z)).
T91 14076-14084 Sentence denotes *Erratum
T92 14085-14126 Sentence denotes Figure 2 was replaced on 7 February 2020.
T93 14128-14230 Sentence denotes Members of the Centre for the Mathematical Modelling of Infectious Diseases (CMMID) nCoV working group
T94 14231-14416 Sentence denotes Yang Liu, Charlie Diamond, W John Edmunds, Sebastian Funk, Amy Gimma, James D Munday, Hamish Gibbs, Nikos I Bosse, Sam Abbott, Timothy W Russell, Petra Klepac, Mark Jit, Joel Hellewell.
T95 14418-14439 Sentence denotes Conflict of interest:
T96 14440-14454 Sentence denotes None declared.
T97 14455-14478 Sentence denotes Authors’ contributions:
T98 14479-14707 Sentence denotes Conceptualisation: BJQ, SF, SC, RME; model formulation: SC, BJQ, SF; analysis: BJQ, SC; writing: RME, SF, SC, BJQ; app testing: RME and the Centre for the Mathematical Modelling of Infectious Diseases (CMMID) nCoV working group.
T99 14708-14919 Sentence denotes The members of the CMMID nCoV working group contributed equally in processing, data cleaning, interpreting findings, testing the interactive tool, reviewing the manuscript and approving the work for publication.
T100 14920-14952 Sentence denotes The order was assigned randomly.