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PMC:7110798 / 677-1921 JSONTXT

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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
12 266-275 Species denotes 2019-nCoV Tax:2697049
13 43-76 Disease denotes coronavirus (2019-nCoV) pneumonia MESH:C000657245
18 426-435 Species denotes 2019-nCoV Tax:2697049
19 663-683 Disease denotes coronavirus diseases MESH:D018352
20 685-689 Disease denotes MERS MESH:D018352
21 694-698 Disease denotes SARS MESH:D045169
24 1104-1113 Species denotes 2019-nCoV Tax:2697049
25 1215-1224 Species denotes 2019-nCoV Tax:2697049

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T2 67-76 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T3 694-698 Disease denotes SARS http://purl.obolibrary.org/obo/MONDO_0005091

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T4 35-36 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T5 81-82 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T1 635-637 Chemical denotes SI http://purl.obolibrary.org/obo/CHEBI_90326
T2 739-741 Chemical denotes SI http://purl.obolibrary.org/obo/CHEBI_90326

LitCovid-PD-GO-BP

Id Subject Object Predicate Lexical cue
T4 238-250 http://purl.obolibrary.org/obo/GO_0000003 denotes reproduction
T5 534-540 http://purl.obolibrary.org/obo/GO_0040007 denotes growth
T6 571-577 http://purl.obolibrary.org/obo/GO_0040007 denotes growth
T7 809-815 http://purl.obolibrary.org/obo/GO_0040007 denotes growth

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T9 0-11 Sentence denotes Backgrounds
T10 12-203 Sentence denotes An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city in China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and other countries.
T11 204-311 Sentence denotes We present estimates of the basic reproduction number, R0, of 2019-nCoV in the early phase of the outbreak.
T12 313-320 Sentence denotes Methods
T13 321-541 Sentence denotes Accounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth.
T14 542-742 Sentence denotes With the estimated intrinsic growth rate (γ), we estimated R0 by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI.
T15 744-752 Sentence denotes Findings
T16 753-816 Sentence denotes The early outbreak data largely follows the exponential growth.
T17 817-871 Sentence denotes We estimated that the mean R0 ranges from 2.24 (95%CI:
T18 872-898 Sentence denotes 1.96–2.55) to 3.58 (95%CI:
T19 899-974 Sentence denotes 2.89–4.39) associated with 8-fold to 2-fold increase in the reporting rate.
T20 975-1059 Sentence denotes We demonstrated that changes in reporting rate substantially affect estimates of R0.
T21 1061-1071 Sentence denotes Conclusion
T22 1072-1175 Sentence denotes The mean estimate of R0 for the 2019-nCoV ranges from 2.24 to 3.58, and is significantly larger than 1.
T23 1176-1244 Sentence denotes Our findings indicate the potential of 2019-nCoV to cause outbreaks.

LitCovid-PD-HP

Id Subject Object Predicate Lexical cue hp_id
T2 67-76 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090