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PMC:7102659 / 1766-5530 JSONTXT

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LitCovid-PD-FMA-UBERON

Id Subject Object Predicate Lexical cue fma_id
T1 1690-1694 Body_part denotes face http://purl.org/sig/ont/fma/fma24728

LitCovid-PD-UBERON

Id Subject Object Predicate Lexical cue uberon_id
T3 1690-1694 Body_part denotes face http://purl.obolibrary.org/obo/UBERON_0001456
T4 2964-2973 Body_part denotes extension http://purl.obolibrary.org/obo/UBERON_2000106

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T9 37-61 Disease denotes coronavirus disease 2019 http://purl.obolibrary.org/obo/MONDO_0100096
T10 63-71 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T11 336-344 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T12 437-445 Disease denotes SARS-CoV http://purl.obolibrary.org/obo/MONDO_0005091
T13 673-681 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T14 1477-1485 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T15 1607-1615 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T16 1710-1718 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T17 1763-1772 Disease denotes influenza http://purl.obolibrary.org/obo/MONDO_0005812
T18 1979-1988 Disease denotes influenza http://purl.obolibrary.org/obo/MONDO_0005812
T19 2089-2098 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T20 2108-2127 Disease denotes influenza infection http://purl.obolibrary.org/obo/MONDO_0005812
T21 2118-2127 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T22 2201-2210 Disease denotes influenza http://purl.obolibrary.org/obo/MONDO_0005812
T23 2306-2315 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T24 2572-2581 Disease denotes influenza http://purl.obolibrary.org/obo/MONDO_0005812

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T6 74-77 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T7 555-556 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T8 716-721 http://purl.obolibrary.org/obo/NCBITaxon_9606 denotes human
T9 805-806 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T10 847-852 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T11 1019-1022 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T12 1031-1038 http://www.ebi.ac.uk/efo/EFO_0000876 denotes extreme
T13 1690-1694 http://purl.obolibrary.org/obo/UBERON_0001456 denotes face
T14 1906-1909 http://purl.obolibrary.org/obo/CLO_0053799 denotes 4–5
T15 2040-2041 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T16 2381-2382 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T17 3333-3334 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T18 3352-3353 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T19 3450-3451 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T20 3533-3534 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T21 3582-3583 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-PD-HP

Id Subject Object Predicate Lexical cue hp_id
T1 2089-2098 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T13 0-12 Sentence denotes Introduction
T14 13-298 Sentence denotes The ongoing outbreak of coronavirus disease 2019 (COVID-19), has claimed 2663 lives, along with 77,658 confirmed cases and 2824 suspected cases in China, as of 24 February 2020 (24:00 GMT+8), according to the National Health Commission of the People's Republic of China (NHCPRC, 2020).
T15 299-637 Sentence denotes The number of deaths associated with COVID-19 greatly exceeds the other two coronaviruses (severe acure respiratory syndrome coronavirus, SARS-CoV, and Middle East respiratory syndrome coronavirus, MERS-CoV), and the outbreak is still ongoing, which posed a huge threat to the global public health and economics (Bogoch et al., 2020, J.T.
T16 638-655 Sentence denotes Wu et al., 2020).
T17 656-853 Sentence denotes The emergence of COVID-19 coincided with the largest annual human migration in the world, i.e., the Spring Festival travel season, which resulted in a rapid national and global spread of the virus.
T18 854-977 Sentence denotes At the early stage of the outbreak, most cases were scattered, and some linked to the Huanan Seafood Wholesale Market (J.T.
T19 978-995 Sentence denotes Wu et al., 2020).
T20 996-1069 Sentence denotes The Chinese government has adopted extreme measures to mitigate outbreak.
T21 1070-1218 Sentence denotes On 23 January 2020, the local government of Wuhan suspended all public traffics within the city, and closed all inbound and outbound transportation.
T22 1219-1332 Sentence denotes Other cities in Hubei province announced similar traffic control measures following Wuhan shortly, see Figure 1 .
T23 1333-1438 Sentence denotes The resumption date in Wuhan remains unclear as of the submission date of this study on 25 February 2020.
T24 1439-1571 Sentence denotes Figure 1 The timeline of the facts of COVID-19 and control measures implemented in Wuhan, China from December 2019 to February 2020.
T25 1572-1669 Sentence denotes The red dots are the events in the COVID-19 outbreak, and the blue dots are the control measures.
T26 1670-1808 Sentence denotes The public panic in face of the ongoing COVID-19 outbreak reminds us the history of the 1918 influenza pandemic in London, United Kingdom.
T27 1809-2030 Sentence denotes Furthermore, its characteristics of mild symptoms in most cases and short serial interval (i.e., 4–5 days) (You et al., 2002; Zhao et al., 2020c) are similar to pandemic influenza, rather than the other two coronaviruses.
T28 2031-2128 Sentence denotes In 1918, a significant proportion of the deaths were from pneumonia followed influenza infection.
T29 2129-2339 Sentence denotes Thus, it might be reasonable to revisit the modelling framework of 1918 influenza pandemic, and in particular, to capture the effects of the individual reaction (to the risk of infection) and government action.
T30 2340-2613 Sentence denotes In (He et al., 2013), the study proposed a model incorporating individual reaction, holiday effects as well as weather conditions (temperature in London, United Kingdom), which successfully captured the multiple-wave feature in the influenza-associated mortality in London.
T31 2614-2852 Sentence denotes In this study, we followed the form of individual reaction and governmental action effects in (He et al., 2013), except for the effects of weather condition due to limited knowledge on weather effects on the transmission of coronaviruses.
T32 2853-3033 Sentence denotes We note that the governmental action, in both 1918 and current time, summarized all measures including holiday extension, city lockdown, hospitalisation and quarantine of patients.
T33 3034-3137 Sentence denotes We presume it will last for the next few months for the moment, and will update later if things change.
T34 3138-3210 Sentence denotes The parameter values may be improved when more information is available.
T35 3211-3386 Sentence denotes We argue that all prevention and control measures may be categorised into two large groups, which are described by either a step function or a response function, respectively.
T36 3387-3505 Sentence denotes We also consider zoonotic transmission period of one month and a huge emigration from Wuhan (35.7% of the population).
T37 3506-3732 Sentence denotes Nevertheless, our model is a preliminary conceptual model, intending to lay a foundation for further modelling studies, but we can easily tune our model so that the outcomes of our model are in line with previous studies (J.T.
T38 3733-3764 Sentence denotes Wu et al., 2020, Mahase, 2020).

LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
27 256-262 Species denotes People Tax:9606
28 375-388 Species denotes coronaviruses Tax:11118
29 424-435 Species denotes coronavirus Tax:11118
30 437-445 Species denotes SARS-CoV Tax:694009
31 451-505 Species denotes Middle East respiratory syndrome coronavirus, MERS-CoV Tax:1335626
32 37-61 Disease denotes coronavirus disease 2019 MESH:C000657245
33 63-71 Disease denotes COVID-19 MESH:C000657245
34 313-319 Disease denotes deaths MESH:D003643
35 336-344 Disease denotes COVID-19 MESH:C000657245
38 1477-1485 Disease denotes COVID-19 MESH:C000657245
39 1607-1615 Disease denotes COVID-19 MESH:C000657245
42 716-721 Species denotes human Tax:9606
43 673-681 Disease denotes COVID-19 MESH:C000657245
50 2016-2029 Species denotes coronaviruses Tax:11118
51 1710-1718 Disease denotes COVID-19 MESH:C000657245
52 2072-2078 Disease denotes deaths MESH:D003643
53 2089-2098 Disease denotes pneumonia MESH:D011014
54 2118-2127 Disease denotes infection MESH:D007239
55 2306-2315 Disease denotes infection MESH:D007239
59 2838-2851 Species denotes coronaviruses Tax:11118
60 3024-3032 Species denotes patients Tax:9606
61 3404-3412 Disease denotes zoonotic MESH:D015047