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PMC:7058650 / 6975-8413 JSONTXT

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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
74 33-42 Species denotes 2019-nCoV Tax:2697049
75 563-569 Species denotes people Tax:9606
76 960-966 Species denotes people Tax:9606
77 1313-1322 Species denotes 2019-nCoV Tax:2697049
78 75-83 Disease denotes infected MESH:D007239
79 194-202 Disease denotes infected MESH:D007239
80 554-562 Disease denotes infected MESH:D007239
81 781-790 Disease denotes infection MESH:D007239
82 951-959 Disease denotes infected MESH:D007239
83 1406-1414 Disease denotes infected MESH:D007239

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T9 781-790 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T38 153-154 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T39 375-376 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T40 445-446 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T41 1091-1092 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T1 981-983 Chemical denotes Cn http://purl.obolibrary.org/obo/CHEBI_33417|http://purl.obolibrary.org/obo/CHEBI_33418|http://purl.obolibrary.org/obo/CHEBI_33517

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T44 0-354 Sentence denotes To estimate the relative risk of 2019-nCoV transmission, we considered all infected passengers who travelled between 1 January and 31 January to possess a maximum risk of transmission 1 (and no infected passengers means no risk) and estimated the relative risk of each country based on the number of passengers who travelled from each of the four cities.
T45 355-475 Sentence denotes Thus countries with a higher number of passengers travelling from any of these cities had a higher risk of transmission.
T46 476-1017 Sentence denotes We then weighted the risk estimated for each city with the number of reported infected people in each city by 31 January 2020 [14] and estimated the mean average risk of transmission termed as ‘Risk index’ which follows the equation below:where x is the destination country, Risk index (x) is the risk of infection importation in country x, P(x)n is the number of passengers to country x from city n, Pn is the total number of passengers who left city n, In is the number of infected people in city n and Cn is the population size of city n.
T47 1018-1177 Sentence denotes The risk index denotes the risk of at least one case being imported into a country or territory where 1 means an absolute certainty and 0 means no risk at all.
T48 1178-1293 Sentence denotes Our model assumed that there is no case outside China and thus ignored if any country already had imported case(s).
T49 1294-1438 Sentence denotes In countries where 2019-nCoV is already detected, the risk index would explain the risk of importing additional infected individuals from China.