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LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T1 23-31 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T2 134-142 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T3 405-413 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T4 427-435 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T5 633-641 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T6 701-709 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T7 722-730 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T8 795-798 Disease denotes MDS http://purl.obolibrary.org/obo/MONDO_0009532|http://purl.obolibrary.org/obo/MONDO_0018881
T10 1034-1037 Disease denotes MDS http://purl.obolibrary.org/obo/MONDO_0009532|http://purl.obolibrary.org/obo/MONDO_0018881
T12 1301-1309 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T13 1677-1685 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T14 1829-1837 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T15 2094-2102 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T1 414-421 http://purl.obolibrary.org/obo/UBERON_0000473 denotes testing
T2 710-717 http://purl.obolibrary.org/obo/UBERON_0000473 denotes testing
T3 933-939 http://purl.obolibrary.org/obo/UBERON_0000473 denotes tested
T4 1014-1019 http://purl.obolibrary.org/obo/UBERON_0000473 denotes tests
T5 1310-1317 http://purl.obolibrary.org/obo/UBERON_0000473 denotes testing
T6 1577-1584 http://purl.obolibrary.org/obo/UBERON_0000473 denotes testing
T7 1631-1632 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T8 1793-1800 http://purl.obolibrary.org/obo/UBERON_0000473 denotes testing
T9 1933-1934 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T10 2067-2077 http://purl.obolibrary.org/obo/UBERON_0000473 denotes testing is

LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
1 23-31 Disease denotes COVID-19 MESH:C000657245
6 134-142 Disease denotes COVID-19 MESH:C000657245
7 259-267 Disease denotes Covid-19 MESH:C000657245
8 405-413 Disease denotes COVID-19 MESH:C000657245
9 427-435 Disease denotes COVID-19 MESH:C000657245
15 633-641 Disease denotes COVID-19 MESH:C000657245
16 701-709 Disease denotes COVID-19 MESH:C000657245
17 722-730 Disease denotes COVID-19 MESH:C000657245
18 741-747 Disease denotes deaths MESH:D003643
19 795-798 Disease denotes MDS MESH:D009190
26 1034-1037 Disease denotes MDS MESH:D009190
27 1301-1309 Disease denotes COVID-19 MESH:C000657245
28 1419-1425 Disease denotes deaths MESH:D003643
29 1677-1685 Disease denotes COVID-19 MESH:C000657245
30 1686-1691 Disease denotes death MESH:D003643
31 1829-1837 Disease denotes COVID-19 MESH:C000657245
33 2094-2102 Disease denotes COVID-19 MESH:C000657245

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T1 0-50 Sentence denotes The 40 health systems, COVID-19 (40HS, C-19) study
T2 52-60 Sentence denotes Abstract
T3 61-69 Sentence denotes Abstract
T4 71-81 Sentence denotes BACKGROUND
T5 82-235 Sentence denotes The health, social and economic consequences of the COVID-19 pandemic have loomed large as every national government made decisions about how to respond.
T6 236-445 Sentence denotes The 40 Health Systems, Covid-19 (40HS.C-19) Study aimed to investigate relationships between governments’ capacity to respond (CTR), their response stringency, scope of COVID-19 testing, and COVID-19 outcomes.
T7 447-454 Sentence denotes METHODS
T8 455-768 Sentence denotes Data to April 2020 were extracted for 40 national health systems on pre-pandemic government capacity to respond (CTR) (Global Competitiveness Index), stringency measures (Oxford COVID-19 Government Response Tracker Stringency Index), approach to COVID-19 testing and COVID-19 cases and deaths (Our-World-in-Data).
T9 769-918 Sentence denotes Multidimensional scaling (MDS) and cluster analysis were applied to examine latent dimensions and visualise country similarities and dissimilarities.
T10 919-1020 Sentence denotes Outcomes were tested using multivariate and one-way analyses of variances and Kruskal-Wallis H tests.
T11 1022-1029 Sentence denotes RESULTS
T12 1030-1154 Sentence denotes The MDS model found three dimensions explaining 91% of the variance and cluster analysis identified five national groupings.
T13 1155-1318 Sentence denotes There was no association between national governments’ pre-pandemic CTR and the adoption of early stringent public health measures or approach to COVID-19 testing.
T14 1319-1426 Sentence denotes Two national clusters applied early stringency measures and reported significantly lower cumulative deaths.
T15 1427-1698 Sentence denotes The best performing national cluster (comprising Australia, South Korea, Iceland and Taiwan) adopted relatively early stringency measures but broader testing earlier than others which was associated with a change in disease trajectory and the lowest COVID-19 death rates.
T16 1699-1847 Sentence denotes Two clusters (one with high CTR and one low) both adopted late stringency measures and narrow testing and performed least well in COVID-19 outcomes.
T17 1849-1859 Sentence denotes CONCLUSION
T18 1860-1961 Sentence denotes Early stringency measures and intrinsic national capacities to deal with a pandemic are insufficient.
T19 1962-2054 Sentence denotes Extended stringency measures, important in the short-term, are not economically sustainable.
T20 2055-2103 Sentence denotes Broad-based testing is key to managing COVID-19.