LitCovid-sentences  

PMC:7001240 / 562-10489 JSONTXT 11 Projects

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Id Subject Object Predicate Lexical cue
T9 0-138 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 139-228 Sentence denotes The infective pathogen was later identified as a novel coronavirus, called 2019-nCoV [2].
T11 229-319 Sentence denotes As at 26 January 2020, a total of 1,988 confirmed cases have been reported from China [3].
T12 320-465 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 466-557 Sentence denotes Forty-one travel-related cases were confirmed as at 27 January 2020, all coming from China.
T14 558-667 Sentence denotes Twenty-seven cases were imported to Asia, six to North America, five to Oceania, and three to Europe [3,5-7].
T15 668-708 Sentence denotes Thirty of them were exported from Wuhan.
T16 709-760 Sentence denotes In Europe, all three cases were imported to France.
T17 761-877 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 878-1026 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 1027-1178 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 1179-1202 Sentence denotes Central European Time).
T21 1203-1261 Sentence denotes This includes a complete ban on international flights [9].
T22 1262-1375 Sentence denotes Here we estimate the risk of importation of 2019-nCoV cases to Europe from infected areas in China by air travel.
T23 1376-1587 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 1589-1618 Sentence denotes Modelling risk of importation
T25 1619-1824 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 1825-1947 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 1948-2149 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 2150-2220 Sentence denotes Details of the computation are provided in the Supplementary Material.
T29 2221-2370 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 2371-2540 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 2541-2652 Sentence denotes For sensitivity, we tested whether the risk changes considering air travel flows of the month of February 2019.
T32 2653-2951 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 2952-2990 Sentence denotes These cities are depicted in Figure 1.
T34 2991-3116 Sentence denotes They were also found to be highly correlated with those reporting a high number of cases in the corresponding provinces [14].
T35 3117-3236 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 3237-3247 Sentence denotes 2019-nCoV:
T37 3248-3266 Sentence denotes Novel coronavirus.
T38 3267-3350 Sentence denotes The 14 cities selected for the multi-source seeding [14] are shown with black dots:
T39 3351-3639 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 3640-3694 Sentence denotes Wuhan (grey dot) is subject to the current travel ban.
T41 3695-4064 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 4065-4135 Sentence denotes Details of the computation are provided in the Supplementary Material.
T43 4136-4310 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 4311-4522 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 4523-4649 Sentence denotes For sensitivity, we also tested whether the risk changes due to the additional inclusion of Wuhan in the multi-source seeding.
T46 4651-4728 Sentence denotes Estimated importation risk from Wuhan before the travel ban in Hubei province
T47 4729-4882 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 4883-5058 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 5059-5294 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 5295-5464 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 5465-5554 Sentence denotes a When a city is served by several airports, these airports are considered as one entity.
T52 5555-5666 Sentence denotes No change was estimated to occur when considering travel flow data from the month of February (data not shown).
T53 5668-5768 Sentence denotes Estimated importation risk from considered areas of China following the travel ban in Hubei province
T54 5769-5961 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 5962-6125 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 6126-6202 Sentence denotes The probability becomes larger than 80% if 60 cases are exported from China.
T57 6203-6577 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 6578-6728 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 6729-6800 Sentence denotes Italy (11%) and Spain (9.5%) rank as fourth and fifth in terms of risk.
T60 6801-6885 Sentence denotes The risk is in general higher in more populated countries (Supplementary Figure S1).
T61 6886-6962 Sentence denotes Also Eastern Europe and Northern Europe would be at risk of importing cases.
T62 6963-7140 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 7141-7230 Sentence denotes a When a city is served by several airports, these airports are considered as one entity.
T64 7231-7361 Sentence denotes For each country, only the four most important cities in terms of agglomeration of airports and passenger traffic are represented.
T65 7362-7400 Sentence denotes Updated to data as at 27 January 2020.
T66 7401-7620 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 7621-7695 Sentence denotes The estimates account for the travel ban imposed in the province of Hubei.
T68 7696-7867 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 7869-7895 Sentence denotes Discussion and conclusions
T70 7896-8085 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 8086-8179 Sentence denotes They are still the first and only imported cases confirmed in Europe, at the time of writing.
T72 8180-8286 Sentence denotes We estimate that the risk of importation of at least one case to Europe except France and Germany is high.
T73 8287-8360 Sentence denotes It is larger than 80% if 60 travel-related cases are exported from China.
T74 8361-8544 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 8545-8666 Sentence denotes Delays are expected from date of importation to date of identification that may bias observations at the time of writing.
T76 8667-8833 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 8834-8985 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 8986-9229 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 9230-9447 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 9448-9631 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 9632-9850 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 9851-9927 Sentence denotes Risk maps will need to be rapidly updated as the outbreak situation evolves.