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PMC:7001240 JSONTXT 23 Projects

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Id Subject Object Predicate Lexical cue
T1 0-82 Sentence denotes Novel coronavirus (2019-nCoV) early-stage importation risk to Europe, January 2020
T2 84-92 Sentence denotes Abstract
T3 93-184 Sentence denotes As at 27 January 2020, 42 novel coronavirus (2019-nCoV) cases were confirmed outside China.
T4 185-280 Sentence denotes We estimate the risk of case importation to Europe from affected areas in China via air travel.
T5 281-370 Sentence denotes We consider travel restrictions in place, three reported cases in France, one in Germany.
T6 371-409 Sentence denotes Estimated risk in Europe remains high.
T7 410-469 Sentence denotes The United Kingdom, Germany and France are at highest risk.
T8 470-560 Sentence denotes Importation from Beijing and Shanghai would lead to higher and widespread risk for Europe.
T9 562-700 Sentence denotes Starting December 2019, cases of pneumonia of unknown aetiology were reported in the city of Wuhan, in the province of Hubei in China [1].
T10 701-790 Sentence denotes The infective pathogen was later identified as a novel coronavirus, called 2019-nCoV [2].
T11 791-881 Sentence denotes As at 26 January 2020, a total of 1,988 confirmed cases have been reported from China [3].
T12 882-1027 Sentence denotes The main affected area is in the province of Hubei, but as at 27 January 2020, confirmed cases have also been reported in 32 other provinces [4].
T13 1028-1119 Sentence denotes Forty-one travel-related cases were confirmed as at 27 January 2020, all coming from China.
T14 1120-1229 Sentence denotes Twenty-seven cases were imported to Asia, six to North America, five to Oceania, and three to Europe [3,5-7].
T15 1230-1270 Sentence denotes Thirty of them were exported from Wuhan.
T16 1271-1322 Sentence denotes In Europe, all three cases were imported to France.
T17 1323-1439 Sentence denotes They were confirmed on 24 January 2020, with travel dates on 18 January 2020 (2 cases) and 22 January 2020 (1 case).
T18 1440-1588 Sentence denotes One case was confirmed in Germany on 27 January 2020 with no history of travel to China but contact with a Chinese guest visiting their company [8].
T19 1589-1740 Sentence denotes In an effort to contain the spread of the virus, Chinese authorities enforced a travel ban in the province of Hubei starting on 23 January 2020 (3 a.m.
T20 1741-1764 Sentence denotes Central European Time).
T21 1765-1823 Sentence denotes This includes a complete ban on international flights [9].
T22 1824-1937 Sentence denotes Here we estimate the risk of importation of 2019-nCoV cases to Europe from infected areas in China by air travel.
T23 1938-2149 Sentence denotes We compare the risk prior to the travel ban in Hubei province, with the risk updated to the outbreak situation of 27 January 2020, accounting for three cases imported to France and one case confirmed in Germany.
T24 2151-2180 Sentence denotes Modelling risk of importation
T25 2181-2386 Sentence denotes For this study, Europe is defined according to the Wikipedia contemporary geographical definition but with exclusion of transcontinental countries (Azerbaijan, Georgia, Kazakhstan, Russia and Turkey) [10].
T26 2387-2509 Sentence denotes The risk of importation to Europe is estimated as the probability that at least one case is imported from China to Europe.
T27 2510-2711 Sentence denotes It is based on estimates from the platform EpiRisk [11] and accounts for origin-destination air travel flows of January 2019 from the Official Airline Guide (OAG) database of the GLEAM Project [11-13].
T28 2712-2782 Sentence denotes Details of the computation are provided in the Supplementary Material.
T29 2783-2932 Sentence denotes To estimate the risk in Europe prior to the travel ban in the Hubei province, we consider Wuhan as the only seed of the international spread [3,5-7].
T30 2933-3102 Sentence denotes We then provide a colour-coded map of Europe to report for each country the probability that a case imported to the continent arrives there, when coming from Wuhan only.
T31 3103-3214 Sentence denotes For sensitivity, we tested whether the risk changes considering air travel flows of the month of February 2019.
T32 3215-3513 Sentence denotes To estimate the risk in Europe following the travel ban, we consider as possible seeds of case exportation out of China the cities that are highly connected to Wuhan based on de-identified and aggregated domestic population movement data (2013–2015) derived from Baidu Location-Based Services [14].
T33 3514-3552 Sentence denotes These cities are depicted in Figure 1.
T34 3553-3678 Sentence denotes They were also found to be highly correlated with those reporting a high number of cases in the corresponding provinces [14].
T35 3679-3798 Sentence denotes Figure 1 Map of Chinese provinces colour coded according to the number of cases of 2019-nCoV [4] as at 27 January 2020
T36 3799-3809 Sentence denotes 2019-nCoV:
T37 3810-3828 Sentence denotes Novel coronavirus.
T38 3829-3912 Sentence denotes The 14 cities selected for the multi-source seeding [14] are shown with black dots:
T39 3913-4201 Sentence denotes Beijing (in the province of Beijing), Changsha (Hunan), Chengdu (Sichuan), Chongqing (Chongqing), Fuzhou (Fujian), Guangzhou (Guangdong), Hangzhou (Zhejiang), Hefei (Anhui), Nanchang (Jiangxi), Nanjing (Jiangsu), Shanghai (Shanghai), Tianjin (Tianjin), Xi’an (Shaanxi), Zhengzhou (Henan).
T40 4202-4256 Sentence denotes Wuhan (grey dot) is subject to the current travel ban.
T41 4257-4626 Sentence denotes To account for the current situation, including the three cases in France and one in Germany, we estimate the risk of importation to Europe except France and Germany as the probability that Europe (France and Germany excluded) imports at least one travel-related case from China, conditioned to the observation of three cases imported to France and one case in Germany.
T42 4627-4697 Sentence denotes Details of the computation are provided in the Supplementary Material.
T43 4698-4872 Sentence denotes We estimate the risk for a varying number of exported cases from China, cumulative in time, to account for likely detection delays or under-detection of travel-related cases.
T44 4873-5084 Sentence denotes As before, we then provide a colour-coded map of Europe to report for each country the probability that a case imported to the continent arrives there, when coming from cities depicted in Figure 1, except Wuhan.
T45 5085-5211 Sentence denotes For sensitivity, we also tested whether the risk changes due to the additional inclusion of Wuhan in the multi-source seeding.
T46 5213-5290 Sentence denotes Estimated importation risk from Wuhan before the travel ban in Hubei province
T47 5291-5444 Sentence denotes The exportation of 30 cases from Wuhan before the travel ban, as reported so far, was estimated to put Europe at 61% risk of importing at least one case.
T48 5445-5620 Sentence denotes The risk was localised in Western European countries, with the highest risk estimated for the United Kingdom (UK; 39%), followed by France (24%), and Germany (15%) (Figure 2).
T49 5621-5856 Sentence denotes In some countries, importations are likely to occur at multiple airports (e.g. Germany, Italy, Spain), whereas in others the risk is mostly concentrated in airports serving the capital city (e.g. London in the UK, and Paris in France).
T50 5857-6026 Sentence denotes Figure 2 (A) Country-specific risk of importation assuming one case imported to Europe from Wuhan before the travel ban, and (B) relative risk by airporta, January 2020
T51 6027-6116 Sentence denotes a When a city is served by several airports, these airports are considered as one entity.
T52 6117-6228 Sentence denotes No change was estimated to occur when considering travel flow data from the month of February (data not shown).
T53 6230-6330 Sentence denotes Estimated importation risk from considered areas of China following the travel ban in Hubei province
T54 6331-6523 Sentence denotes The probability that at least one case is imported to Europe except France and Germany, given the three imported cases reported in France and one case confirmed in Germany, is high (Figure 3).
T55 6524-6687 Sentence denotes It is estimated to be more than 64% for the number of travel-related exportations from China reported so far (41 travel-related and one confirmed case in Germany).
T56 6688-6764 Sentence denotes The probability becomes larger than 80% if 60 cases are exported from China.
T57 6765-7139 Sentence denotes Figure 3 Risk, as a function of the cumulative number of exported cases from China, of importing at least one case to Europe except France and Germany, given three imported cases reported in France and one case confirmed in Germany, January 2020 In the event that one travel-related case is imported to Europe, the risk of importation is highest in the UK (25%) (Figure 4).
T58 7140-7290 Sentence denotes Germany and France, which already have confirmed cases, rank second and third with a probability of 16% and 13% to receive another case, respectively.
T59 7291-7362 Sentence denotes Italy (11%) and Spain (9.5%) rank as fourth and fifth in terms of risk.
T60 7363-7447 Sentence denotes The risk is in general higher in more populated countries (Supplementary Figure S1).
T61 7448-7524 Sentence denotes Also Eastern Europe and Northern Europe would be at risk of importing cases.
T62 7525-7702 Sentence denotes Figure 4 (A) Country-specific risk of importation assuming one case imported to Europe from the multi-source seeding of Figure 1 and (B) relative risk by airporta, January 2020
T63 7703-7792 Sentence denotes a When a city is served by several airports, these airports are considered as one entity.
T64 7793-7923 Sentence denotes For each country, only the four most important cities in terms of agglomeration of airports and passenger traffic are represented.
T65 7924-7962 Sentence denotes Updated to data as at 27 January 2020.
T66 7963-8182 Sentence denotes In the UK and France, the airports serving the capital cities continue to contribute the largest likelihood of importing cases (London contributes to 83% of the risk, Paris contributes to 94% of the risk, respectively).
T67 8183-8257 Sentence denotes The estimates account for the travel ban imposed in the province of Hubei.
T68 8258-8429 Sentence denotes Including travel flows from Wuhan, to account for cases who may have flown before the travel ban and are not yet detected, does not alter the estimations (data not shown).
T69 8431-8457 Sentence denotes Discussion and conclusions
T70 8458-8647 Sentence denotes France reported on 24 January 2020 the importation of three 2019-nCoV confirmed cases from China, and Germany confirmed its first case on 27 January 2020 with no history of travel to China.
T71 8648-8741 Sentence denotes They are still the first and only imported cases confirmed in Europe, at the time of writing.
T72 8742-8848 Sentence denotes We estimate that the risk of importation of at least one case to Europe except France and Germany is high.
T73 8849-8922 Sentence denotes It is larger than 80% if 60 travel-related cases are exported from China.
T74 8923-9106 Sentence denotes The three countries at highest risk are the UK, Germany, and France (confirming estimates reported by other studies [12,14,15]), with the latter two countries already reporting cases.
T75 9107-9228 Sentence denotes Delays are expected from date of importation to date of identification that may bias observations at the time of writing.
T76 9229-9395 Sentence denotes All three cases imported to France were confirmed on 24 January 2020, with two travelling on 18 January 2020 (6 days delay) and one on 22 January 2020 (2 days delay).
T77 9396-9547 Sentence denotes The risk pattern of 2019-nCoV importation estimated for Europe varies considerably depending on the geographical extent of the affected areas in China.
T78 9548-9791 Sentence denotes In particular, a larger area acting as seed of exportation that includes Shanghai and Beijing (two cities with larger number of travellers to more widespread areas in Europe) would likely result in a higher and more widespread risk for Europe.
T79 9792-10009 Sentence denotes Our results are based on available data and estimates of the affected provinces in China and account for origin-destination travel fluxes from these provinces, as well as the travel ban enforced in the Hubei province.
T80 10010-10193 Sentence denotes However, estimates are sensitive to different health-seeking behaviours that infected travellers may have, and to the active surveillance practices put in place in European countries.
T81 10194-10412 Sentence denotes We did not provide estimates of the expected number of imported cases per country, as this depends on the number of travel-related exported cases from China, a variable that is still hard to assess at this early stage.
T82 10413-10489 Sentence denotes Risk maps will need to be rapidly updated as the outbreak situation evolves.
T83 10491-10507 Sentence denotes Acknowledgements
T84 10508-10641 Sentence denotes We thank the GLEAM Project for the use of EpiRisk, Simon Cauchemez and REACTing (https://reacting.inserm.fr/) for useful discussions.
T85 10642-10660 Sentence denotes Funding statement:
T86 10661-10792 Sentence denotes This study was partially supported by the ANR project DATAREDUX (ANR-19-CE46-0008-03) to VC; the H2020 MOOD project to VC, CP, PYB.
T87 10794-10815 Sentence denotes Conflict of interest:
T88 10816-10830 Sentence denotes None declared.
T89 10831-10889 Sentence denotes Authors’ contributions: GP, FP, EV performed the analysis.
T90 10890-10942 Sentence denotes EV, PYB, CP, VC conceived and designed the analysis.
T91 10943-10967 Sentence denotes VC wrote the manuscript.
T92 10969-10987 Sentence denotes Supplementary Data
T93 10988-11010 Sentence denotes Supplementary Material
T94 11011-11047 Sentence denotes Click here for additional data file.