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PMC:7033348 / 7542-8650 JSONTXT

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LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T10 189-199 Disease denotes infectious http://purl.obolibrary.org/obo/MONDO_0005550
T11 220-224 Disease denotes SARS http://purl.obolibrary.org/obo/MONDO_0005091
T12 226-231 Disease denotes Ebola http://purl.obolibrary.org/obo/MONDO_0005737
T13 242-251 Disease denotes influenza http://purl.obolibrary.org/obo/MONDO_0005812
T14 257-263 Disease denotes dengue http://purl.obolibrary.org/obo/MONDO_0005502
T15 851-855 Disease denotes SARS http://purl.obolibrary.org/obo/MONDO_0005091

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T38 155-156 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T39 309-313 http://purl.obolibrary.org/obo/CLO_0001185 denotes 2018
T40 477-478 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T41 580-581 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T42 601-602 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T43 729-730 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T44 1032-1033 http://purl.obolibrary.org/obo/CLO_0001020 denotes A

LitCovid-PD-GO-BP

Id Subject Object Predicate Lexical cue
T5 365-371 http://purl.obolibrary.org/obo/GO_0040007 denotes growth
T6 412-418 http://purl.obolibrary.org/obo/GO_0040007 denotes growth
T7 456-462 http://purl.obolibrary.org/obo/GO_0040007 denotes growth
T8 490-496 http://purl.obolibrary.org/obo/GO_0040007 denotes growth

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T44 0-6 Sentence denotes Models
T45 7-339 Sentence denotes We generate short-term forecasts in real-time using three phenomenological models that have been previously used to derive short-term forecasts for a number of epidemics for several infectious diseases, including SARS, Ebola, pandemic influenza, and dengue (Chowell, Tariq, & Hyman, 2019; Pell et al., 2018; Wang, Wu, & Yang, 2012).
T46 340-546 Sentence denotes The generalized logistic growth model (GLM) extends the simple logistic growth model to accommodate sub-exponential growth dynamics with a scaling of growth parameter, p (Viboud, Simonsen, & Chowell, 2016).
T47 547-712 Sentence denotes The Richards model also includes a scaling parameter, a, to allow for deviation from the symmetric logistic curve (Chowell, 2017; Richards, 1959; Wang et al., 2012).
T48 713-893 Sentence denotes We also include a recently developed sub-epidemic wave model that supports complex epidemic trajectories, including multiple peaks (i.e., SARS in Singapore (Chowell et al., 2019)).
T49 894-1031 Sentence denotes In this approach, the observed reported curve is assumed to be the aggregate of multiple underlying sub-epidemics (Chowell et al., 2019).
T50 1032-1108 Sentence denotes A detailed description for each of the models is included in the Supplement.

LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
27 189-208 Disease denotes infectious diseases MESH:D003141
28 220-224 Disease denotes SARS MESH:D045169
29 851-855 Disease denotes SARS MESH:D045169

2_test

Id Subject Object Predicate Lexical cue
32110742-27913131-47437629 309-313 27913131 denotes 2018
32110742-22889641-47437630 333-337 22889641 denotes 2012
32110742-27266847-47437631 540-544 27266847 denotes 2016
32110742-22889641-47437632 706-710 22889641 denotes 2012
T48089 309-313 27913131 denotes 2018
T63529 333-337 22889641 denotes 2012
T61091 540-544 27266847 denotes 2016
T25904 706-710 22889641 denotes 2012