> top > docs > PMC:7078825 > spans > 9075-14258 > annotations

PMC:7078825 / 9075-14258 JSONTXT

Annnotations TAB JSON ListView MergeView

LitCovid-PMC-OGER-BB

Id Subject Object Predicate Lexical cue
T50 140-151 NCBITaxon:11118 denotes coronavirus
T49 274-282 SP_7 denotes COVID-19
T48 466-474 SP_7 denotes COVID-19
T47 624-632 SP_7 denotes COVID-19
T46 1176-1188 GO:0065007 denotes surveillance
T45 1359-1370 UBERON:0001004 denotes respiratory
T44 1554-1561 GO:0065007 denotes control
T43 1655-1666 UBERON:0001004 denotes respiratory
T42 1823-1831 SP_7 denotes COVID-19
T41 1920-1928 SP_7 denotes COVID-19
T40 2039-2047 SP_7 denotes COVID-19
T39 2128-2133 GO:0007612 denotes learn
T38 2144-2149 NCBITaxon:10239 denotes virus
T36 2549-2560 NCBITaxon:11118 denotes coronavirus
T35 3415-3423 SP_7 denotes COVID-19
T34 3563-3574 NCBITaxon:11118 denotes coronavirus
T33 3654-3665 NCBITaxon:11118 denotes coronavirus
T32 3721-3732 NCBITaxon:11118 denotes coronavirus
T31 3761-3769 SP_7 denotes COVID-19
T30 3920-3931 NCBITaxon:11118 denotes coronavirus
T29 3993-4001 SP_7 denotes COVID-19
T28 4063-4074 NCBITaxon:11118 denotes coronavirus
T27 4095-4106 NCBITaxon:11118 denotes coronavirus
T26 4359-4370 NCBITaxon:11118 denotes coronavirus
T25 4664-4675 NCBITaxon:11118 denotes coronavirus
T24 4694-4699 NCBITaxon:10239 denotes viral
T37 2229-2237 SP_7 denotes COVID-19

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T31 158-167 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T32 274-282 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T33 466-474 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T34 624-632 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T35 656-674 Disease denotes infectious disease http://purl.obolibrary.org/obo/MONDO_0005550
T36 1278-1287 Disease denotes influenza http://purl.obolibrary.org/obo/MONDO_0005812
T37 1293-1305 Disease denotes dengue fever http://purl.obolibrary.org/obo/MONDO_0005502
T38 1321-1325 Disease denotes Zika http://purl.obolibrary.org/obo/MONDO_0018661
T39 1331-1338 Disease denotes measles http://purl.obolibrary.org/obo/MONDO_0004619
T40 1429-1439 Disease denotes infectious http://purl.obolibrary.org/obo/MONDO_0005550
T41 1823-1831 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T42 1920-1928 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T43 2039-2047 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T44 2229-2237 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T45 3415-3423 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T46 3449-3458 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T47 3485-3494 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T48 3666-3675 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T49 3721-3745 Disease denotes coronavirus disease 2019 http://purl.obolibrary.org/obo/MONDO_0100096
T50 3761-3769 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T51 3904-3913 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T52 3993-4001 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T53 4107-4116 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T54 4472-4481 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T55 4767-4776 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T24 501-504 http://purl.obolibrary.org/obo/CLO_0050236 denotes lag
T25 524-525 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T26 636-637 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T27 735-736 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T28 1234-1237 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T29 1748-1749 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T30 1762-1765 http://purl.obolibrary.org/obo/CLO_0050236 denotes lag
T31 1852-1859 http://www.ebi.ac.uk/efo/EFO_0000881 denotes digital
T32 1932-1933 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T33 1995-1996 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T34 2144-2149 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T35 2287-2292 http://purl.obolibrary.org/obo/UBERON_0000473 denotes tests
T36 2366-2369 http://purl.obolibrary.org/obo/CLO_0050236 denotes lag
T37 2482-2489 http://purl.obolibrary.org/obo/UBERON_0000473 denotes testing
T38 3061-3062 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T39 3110-3111 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T40 3335-3336 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T41 3555-3556 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T42 3775-3777 http://purl.obolibrary.org/obo/CLO_0053733 denotes 11
T43 3857-3859 http://purl.obolibrary.org/obo/CLO_0053733 denotes 11
T44 4741-4742 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T45 4754-4758 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T46 4781-4782 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T47 4894-4895 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T48 5015-5016 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T49 5065-5068 http://purl.obolibrary.org/obo/CLO_0050236 denotes lag
T50 5083-5084 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T51 5169-5170 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T2 199-202 Chemical denotes NHC http://purl.obolibrary.org/obo/CHEBI_51369
T3 492-495 Chemical denotes NHC http://purl.obolibrary.org/obo/CHEBI_51369
T4 3015-3018 Chemical denotes NHC http://purl.obolibrary.org/obo/CHEBI_51369
T5 3683-3686 Chemical denotes NHC http://purl.obolibrary.org/obo/CHEBI_51369

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T71 0-10 Sentence denotes Discussion
T72 11-310 Sentence denotes Our study demonstrated that the data obtained from Google Trends, Baidu Index and Sina Weibo Index on searches for the keywords ‘coronavirus’ and ‘pneumonia’ correlated with the published NHC data on daily incidence of laboratory-confirmed and suspected cases of COVID-19, with the maximum r > 0.89.
T73 311-496 Sentence denotes We also found that the peak interest for these keywords in Internet search engines and social media data was 10–14 days earlier than the incidence peak of COVID-19 published by the NHC.
T74 497-623 Sentence denotes The lag correlation showed a maximum correlation at 8–12 days for laboratory-confirmed cases and 6–8 days for suspected cases.
T75 624-776 Sentence denotes COVID-19 is a rapidly spreading infectious disease with, at the time of submission, more than 80,000 cases and a mortality so far known to be 3.4% [10].
T76 777-921 Sentence denotes It is important to predict the development of this outbreak as early and as reliably as possible, in order to take action to prevent its spread.
T77 922-1154 Sentence denotes Our data showed that the two popularly used Internet search engines, Google and Baidu, and the social media platform, Sina Weibo, were able to predict the disease outbreak 1–2 weeks earlier than the traditional surveillance systems.
T78 1155-1384 Sentence denotes The role of Internet surveillance tools in early prediction of other epidemics has been reported previously, including for influenza [4], dengue fever [5], H1N1 [6], Zika [7], measles [8] and Middle East respiratory syndrome [9].
T79 1385-1577 Sentence denotes The availability of early information about infectious diseases through Internet search engines and social media will be helpful for making decisions related to disease control and prevention.
T80 1578-1719 Sentence denotes Internet search data have been shown to enable the monitoring of Middle East respiratory syndrome 3 days before laboratory confirmations [9].
T81 1720-1878 Sentence denotes However, our results showed a much longer lag time for reported new laboratory-confirmed and suspected COVID-19 cases compared with digital surveillance data.
T82 1879-1910 Sentence denotes There are several explanations.
T83 1911-1973 Sentence denotes Firstly, COVID-19 is a novel disease just recently recognised.
T84 1974-2081 Sentence denotes The first version of a guideline for diagnosis and management of COVID-19 was announced on 16 January 2020.
T85 2082-2201 Sentence denotes It took time for the medical professionals to learn about the virus and the disease in order to make correct diagnosis.
T86 2202-2337 Sentence denotes Secondly, the diagnosis of COVID-19 requires two independent confirmatory laboratory tests, which should be taken at least 1 day apart.
T87 2338-2447 Sentence denotes Our results showed that the lag correlation is shorter for the suspected than for laboratory-confirmed cases.
T88 2448-2641 Sentence denotes Thirdly, the supply of laboratory testing kits may have been insufficient in the early stages of the coronavirus outbreak, which would have limited the number of patients that can be confirmed.
T89 2642-2859 Sentence denotes Finally, the Internet searches and social media mentions are not only initiated by the patients and their family members, but also globally by the general public who are concerned about this rapidly spreading disease.
T90 2860-3060 Sentence denotes In addition, we found that the data from the Baidu Index and Sina Weibo Index could monitor the number of daily new confirmed and suspected cases from the NHC earlier than the data from Google Trends.
T91 3061-3190 Sentence denotes A possible explanation is that the Google is not a major search engine used in China, where Baidu and Sina Weibo are widely used.
T92 3191-3282 Sentence denotes The peak in the Sina Weibo Index was reached earlier than in Google Trends and Baidu Index.
T93 3283-3414 Sentence denotes This suggests that Sina Weibo, which also serves as a social medium, disseminated the information faster than traditional websites.
T94 3415-3535 Sentence denotes COVID-19 was firstly reported as ‘pneumonia of unknown aetiology’ or ‘pneumonia of unknown cause’ in late December 2019.
T95 3536-3619 Sentence denotes On 8 January 2020, a novel coronavirus was identified as the cause of this disease.
T96 3620-3798 Sentence denotes The disease was first named Novel coronavirus pneumonia by the NHC of China on 8 February and later ‘coronavirus disease 2019’ (abbreviated ‘COVID-19’) on 11 February by the WHO.
T97 3799-3860 Sentence denotes Our search period was defined from January 16 to February 11.
T98 3861-4017 Sentence denotes Therefore, we think that the two keywords ‘pneumonia’ and ‘coronavirus’ were sufficient to include most Internet content related to COVID-19 in this period.
T99 4018-4244 Sentence denotes We also used other terms such as ‘新冠‘ (novel coronavirus), ‘新型冠状病毒肺炎’ (novel coronavirus pneumonia) as keywords but they returned much smaller numbers of queries and posts and we did therefore not include them in the analysis.
T100 4245-4334 Sentence denotes It is also notable that the strength of correlation was different for different keywords.
T101 4335-4566 Sentence denotes On Google, the keyword ‘coronavirus’ had the highest correlation coefficient (r = 0.958) with daily new laboratory-confirmed cases, and ‘pneumonia’ had the highest correlation coefficient with daily new suspected cases (r = 0.960).
T102 4567-4633 Sentence denotes We found the same pattern in the Baidu Index and Sina Weibo Index.
T103 4634-4893 Sentence denotes An explanation could be that ‘coronavirus’ is linked to the viral pathogen which should be investigated by a laboratory test, while ‘pneumonia’ is a clinical term and should link stronger to the suspected cases that are based on clinical and imaging evidence.
T104 4894-4948 Sentence denotes A limitation of our study is its retrospective nature.
T105 4949-5183 Sentence denotes If the Internet search engines and social media data were used in a real-time surveillance system, finding the best lag time would be a challenge because we would not have any training data to calibrate the analysis for a new disease.

LitCovid-PD-HP

Id Subject Object Predicate Lexical cue hp_id
T15 158-167 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T16 1300-1305 Phenotype denotes fever http://purl.obolibrary.org/obo/HP_0001945
T17 3449-3458 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T18 3485-3494 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T19 3666-3675 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T20 3904-3913 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T21 4107-4116 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T22 4472-4481 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T23 4767-4776 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090

2_test

Id Subject Object Predicate Lexical cue
32183935-19020500-29321489 1289-1290 19020500 denotes 4
32183935-28719659-29321490 1307-1308 28719659 denotes 5
32183935-19941777-29321491 1317-1318 19941777 denotes 6
32183935-27251981-29321492 1327-1328 27251981 denotes 7
32183935-31268123-29321493 1340-1341 31268123 denotes 8
32183935-27595921-29321494 1381-1382 27595921 denotes 9
32183935-27595921-29321495 1716-1717 27595921 denotes 9

LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
107 93-97 Species denotes Sina Tax:647292
108 140-151 Species denotes coronavirus Tax:11118
109 158-167 Disease denotes pneumonia MESH:D011014
110 274-282 Disease denotes COVID-19 MESH:C000657245
111 466-474 Disease denotes COVID-19 MESH:C000657245
120 1040-1044 Species denotes Sina Tax:647292
122 624-632 Disease denotes COVID-19 MESH:C000657245
123 656-674 Disease denotes infectious disease MESH:D003141
124 737-746 Disease denotes mortality MESH:D003643
125 1300-1305 Disease denotes fever MESH:D005334
126 1347-1379 Disease denotes Middle East respiratory syndrome MESH:D018352
127 1429-1448 Disease denotes infectious diseases MESH:D003141
136 2549-2560 Species denotes coronavirus Tax:11118
137 2610-2618 Species denotes patients Tax:9606
138 2729-2737 Species denotes patients Tax:9606
139 1643-1675 Disease denotes Middle East respiratory syndrome MESH:D018352
140 1823-1831 Disease denotes COVID-19 MESH:C000657245
141 1920-1928 Disease denotes COVID-19 MESH:C000657245
142 2039-2047 Disease denotes COVID-19 MESH:C000657245
143 2229-2237 Disease denotes COVID-19 MESH:C000657245
148 2921-2925 Species denotes Sina Tax:647292
149 3163-3167 Species denotes Sina Tax:647292
150 3207-3211 Species denotes Sina Tax:647292
151 3302-3306 Species denotes Sina Tax:647292
164 3557-3574 Species denotes novel coronavirus Tax:2697049
165 3920-3931 Species denotes coronavirus Tax:11118
166 4057-4074 Species denotes novel coronavirus Tax:2697049
167 3415-3423 Disease denotes COVID-19 MESH:C000657245
168 3449-3458 Disease denotes pneumonia MESH:D011014
169 3485-3494 Disease denotes pneumonia MESH:D011014
170 3648-3675 Disease denotes Novel coronavirus pneumonia MESH:C000657245
171 3721-3745 Disease denotes coronavirus disease 2019 MESH:C000657245
172 3761-3769 Disease denotes COVID-19 MESH:C000657245
173 3904-3913 Disease denotes pneumonia MESH:D011014
174 3993-4001 Disease denotes COVID-19 MESH:C000657245
175 4089-4116 Disease denotes novel coronavirus pneumonia MESH:C000657245
181 4359-4370 Species denotes coronavirus Tax:11118
182 4616-4620 Species denotes Sina Tax:647292
183 4664-4675 Species denotes coronavirus Tax:11118
184 4472-4481 Disease denotes pneumonia MESH:D011014
185 4767-4776 Disease denotes pneumonia MESH:D011014

MyTest

Id Subject Object Predicate Lexical cue
32183935-19020500-29321489 1289-1290 19020500 denotes 4
32183935-28719659-29321490 1307-1308 28719659 denotes 5
32183935-19941777-29321491 1317-1318 19941777 denotes 6
32183935-27251981-29321492 1327-1328 27251981 denotes 7
32183935-31268123-29321493 1340-1341 31268123 denotes 8
32183935-27595921-29321494 1381-1382 27595921 denotes 9
32183935-27595921-29321495 1716-1717 27595921 denotes 9