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LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T1 27-35 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T2 234-252 Disease denotes infectious disease http://purl.obolibrary.org/obo/MONDO_0005550
T3 258-282 Disease denotes Coronavirus Disease 2019 http://purl.obolibrary.org/obo/MONDO_0100096
T4 284-292 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T5 622-630 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T6 778-786 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T7 882-890 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T8 973-982 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T9 1125-1133 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T10 1357-1365 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T11 1417-1425 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T12 1528-1536 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T13 1674-1682 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T14 1708-1716 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T15 2151-2159 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T16 2255-2263 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T17 2300-2308 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T18 2356-2364 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T19 2444-2452 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T20 2871-2879 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T21 2981-2989 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T22 3356-3364 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T23 3502-3510 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T24 3572-3576 Disease denotes SARS http://purl.obolibrary.org/obo/MONDO_0005091
T25 3886-3894 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T26 4098-4106 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T27 4131-4139 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T28 4443-4451 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T29 5130-5138 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T1 111-114 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T2 294-297 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T3 591-592 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T4 953-956 http://purl.obolibrary.org/obo/CLO_0050884 denotes Ten
T5 1083-1085 http://purl.obolibrary.org/obo/CLO_0053755 denotes ES
T6 1197-1198 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T7 1557-1562 http://purl.obolibrary.org/obo/UBERON_0000473 denotes tests
T8 1641-1643 http://purl.obolibrary.org/obo/CLO_0050507 denotes 22
T9 2242-2243 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T10 2323-2324 http://purl.obolibrary.org/obo/CLO_0001021 denotes B
T11 2833-2834 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T12 3751-3752 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T13 4415-4418 http://purl.obolibrary.org/obo/CLO_0051582 denotes has

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T1 1083-1085 Chemical denotes ES http://purl.obolibrary.org/obo/CHEBI_73509

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T1 0-68 Sentence denotes Can Google® trends predict COVID-19 incidence and help preparedness?
T2 69-94 Sentence denotes The situation in Colombia
T3 96-107 Sentence denotes Dear Editor
T4 108-253 Sentence denotes As has been stated by Aschwanden et al. [1], social media and communication can track public interest or concern regarding an infectious disease.
T5 254-321 Sentence denotes The Coronavirus Disease 2019 (COVID-19) has not been the exception.
T6 322-555 Sentence denotes This emerging disease began to cause global concern since it attracted global concern in December 2019 [2], but clearly, in multiple countries the preoccupation was associated with its spreading in other countries in Asia and beyond.
T7 556-684 Sentence denotes This relationship appeared to have a sharp impact especially when COVID-19 cases arrived and increased rapidly in the countries.
T8 685-881 Sentence denotes Here, we would like to show the findings of an assessment regarding the relationship between COVID-19 cases and Google ® searches, using the Google ® Trends tool, in Colombia up to March 28, 2020.
T9 882-952 Sentence denotes COVID-19 arrived in Latin America on February 25, 2020, to Brazil [3].
T10 953-1013 Sentence denotes Ten days later, the infection made it to Colombia (Fig. 1 ).
T11 1014-1207 Sentence denotes Using the Google ® Trends tool (https://trends.google.es/trends/?geo=ES) we found that in Colombia searches on COVID-19 begun on January 21, 2020, as the global situation begun to be a concern.
T12 1208-1300 Sentence denotes After the first case in the country, the searches started to considerably increase (Fig. 1).
T13 1301-1473 Sentence denotes There is high relationship after this point between the COVID-19 incidence in Colombia and the Google ® searches on COVID-19 in Colombia (r2 = 0.8728, p < 0.0001) (Fig. 1).
T14 1474-1580 Sentence denotes As of March 28, 2020, Colombia confirmed 702 cases of COVID-19 from 10,648 rRT-PCR tests performed (6.6%).
T15 1581-1683 Sentence denotes At that time, from 32 departments and the capital district, 22 departments reported cases of COVID-19.
T16 1684-1863 Sentence denotes Looking the searches of COVID-19 by department, they were also highly associated with the number of cases reported at that administrative level (r2 = 0.9740, p < 0.0001) (Fig. 1).
T17 1864-2018 Sentence denotes We ran non-linear regressions, using the best fitted model, on Stata 14IC® licensed for Universidad Tecnologica de Pereira, Colombia, p significant <0.05.
T18 2019-2143 Sentence denotes Epidemiological data was obtained from the public web site of the National Institute of Health of Colombia (www.ins.gov.co).
T19 2144-2241 Sentence denotes Fig. 1 COVID-19 incidence in Colombia and Google ® searches, December 29, 2019 to March 28, 2020.
T20 2242-2244 Sentence denotes A.
T21 2245-2322 Sentence denotes Trends in COVID-19 Cases (red) and Google® searches on COVID-19, in Colombia.
T22 2323-2325 Sentence denotes B.
T23 2326-2410 Sentence denotes Non-linear regression between COVID-19 incidence and searches in Colombia, by dates.
T24 2411-2413 Sentence denotes C.
T25 2414-2635 Sentence denotes Non-linear regression between COVID-19 incidence and searches in Colombia, by departments. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
T26 2636-2832 Sentence denotes Internet searches and social media data have been reported to correlate with traditional surveillance data and can even predict the outbreak of disease epidemics several days or weeks earlier [4].
T27 2833-3030 Sentence denotes A recent study found that searches on COVID-19 correlated with the published data on daily incidence of laboratory-confirmed and suspected cases of COVID-19 in China, with the maximum r > 0.89 [4].
T28 3031-3268 Sentence denotes Also, in Taiwan, in response to the ongoing outbreak, analyses demonstrated that Google ® Trends could potentially define the proper timing and location for practicing appropriate risk communication strategies to the affected population.
T29 3269-3411 Sentence denotes Authors found high to moderate correlations between Google® relative search volume and COVID-19 cases by administrative levels, as we did [5].
T30 3412-3515 Sentence denotes In Iran, the linear regression model using the Google ® Trends predicted the incidence of COVID-19 [6].
T31 3516-3698 Sentence denotes In previous outbreaks due to coronaviruses, such as the SARS and MERS, in 2002 and 2012, different approaches were used to predict outbreaks using social media and Google ® searches.
T32 3699-3895 Sentence denotes Despite the studies mentioned above, there is still a lack of publications, on this theme, in Latin America [7], and there are no similar assessments in other countries of the region for COVID-19.
T33 3896-4111 Sentence denotes We suggest that in countries with lack of diagnostic and surveillance capacity, as is the case of Venezuela and Haiti, the use of Google ® Trends would be used to see changes in the searches related to COVID-19 [3].
T34 4112-4336 Sentence denotes As the pandemic of COVID-19 impacted more on the life of people in Colombia, and probably of Latin America, more searches were gradually observed, reflecting the interest of people to be informed about this emerging disease.
T35 4337-4480 Sentence denotes Up to April 28, 2020 (the date of proofs correction of this letter), Colombia has reported 5,949 cases of COVID-19, with 269 associated deaths.
T36 4482-4522 Sentence denotes CRediT authorship contribution statement
T37 4523-4545 Sentence denotes Yeimer Ortiz-Martínez:
T38 4546-4618 Sentence denotes Data curation, Formal analysis, Methodology, Writing - review & editing.
T39 4619-4647 Sentence denotes Juan Esteban Garcia-Robledo:
T40 4648-4675 Sentence denotes Writing - review & editing.
T41 4676-4684 Sentence denotes Danna L.
T42 4685-4703 Sentence denotes Vásquez-Castañeda:
T43 4704-4731 Sentence denotes Writing - review & editing.
T44 4732-4734 Sentence denotes D.
T45 4735-4760 Sentence denotes Katterine Bonilla-Aldana:
T46 4761-4788 Sentence denotes Writing - review & editing.
T47 4789-4799 Sentence denotes Alfonso J.
T48 4800-4818 Sentence denotes Rodriguez-Morales:
T49 4819-4946 Sentence denotes Conceptualization, Data curation, Formal analysis, Methodology, Software, Writing - original draft, Writing - review & editing.
T50 4948-4981 Sentence denotes Declaration of competing interest
T51 4982-5029 Sentence denotes We declare that we have no competing interests.
T52 5031-5046 Sentence denotes Acknowledgments
T53 5047-5184 Sentence denotes To the National Institute of Health of Colombia for providing publicly the data of COVID-19 surveillance in its website (www.ins.gov.co).

LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
1 27-35 Disease denotes COVID-19 MESH:C000657245
7 234-252 Disease denotes infectious disease MESH:D003141
8 258-282 Disease denotes Coronavirus Disease 2019 MESH:C000657245
9 284-292 Disease denotes COVID-19 MESH:C000657245
10 622-630 Disease denotes COVID-19 MESH:C000657245
11 778-786 Disease denotes COVID-19 MESH:C000657245
17 2151-2159 Disease denotes COVID-19 MESH:C000657245
18 2255-2263 Disease denotes COVID-19 MESH:C000657245
19 2300-2308 Disease denotes COVID-19 MESH:C000657245
20 2356-2364 Disease denotes COVID-19 MESH:C000657245
21 2444-2452 Disease denotes COVID-19 MESH:C000657245
30 882-890 Disease denotes COVID-19 MESH:C000657245
31 973-982 Disease denotes infection MESH:D007239
32 1125-1133 Disease denotes COVID-19 MESH:C000657245
33 1357-1365 Disease denotes COVID-19 MESH:C000657245
34 1417-1425 Disease denotes COVID-19 MESH:C000657245
35 1528-1536 Disease denotes COVID-19 MESH:C000657245
36 1674-1682 Disease denotes COVID-19 MESH:C000657245
37 1708-1716 Disease denotes COVID-19 MESH:C000657245
45 3545-3558 Species denotes coronaviruses Tax:11118
46 2871-2879 Disease denotes COVID-19 MESH:C000657245
47 2981-2989 Disease denotes COVID-19 MESH:C000657245
48 3356-3364 Disease denotes COVID-19 MESH:C000657245
49 3502-3510 Disease denotes COVID-19 MESH:C000657245
50 3572-3576 Disease denotes SARS MESH:D045169
51 3581-3585 Disease denotes MERS MESH:D018352
59 4169-4175 Species denotes people Tax:9606
60 4286-4292 Species denotes people Tax:9606
61 3886-3894 Disease denotes COVID-19 MESH:C000657245
62 4098-4106 Disease denotes COVID-19 MESH:C000657245
63 4131-4139 Disease denotes COVID-19 MESH:C000657245
64 4443-4451 Disease denotes COVID-19 MESH:C000657245
65 4473-4479 Disease denotes deaths MESH:D003643