PMC:7510993 / 182-871
Annnotations
LitCovid-PD-MONDO
| Id | Subject | Object | Predicate | Lexical cue | mondo_id |
|---|---|---|---|---|---|
| T3 | 24-48 | Disease | denotes | coronavirus disease 2019 | http://purl.obolibrary.org/obo/MONDO_0100096 |
| T4 | 50-58 | Disease | denotes | COVID-19 | http://purl.obolibrary.org/obo/MONDO_0100096 |
| T5 | 181-189 | Disease | denotes | COVID-19 | http://purl.obolibrary.org/obo/MONDO_0100096 |
| T6 | 231-238 | Disease | denotes | malaria | http://purl.obolibrary.org/obo/MONDO_0005136 |
| T7 | 408-416 | Disease | denotes | COVID-19 | http://purl.obolibrary.org/obo/MONDO_0100096 |
| T8 | 594-602 | Disease | denotes | COVID-19 | http://purl.obolibrary.org/obo/MONDO_0100096 |
| T9 | 666-674 | Disease | denotes | COVID-19 | http://purl.obolibrary.org/obo/MONDO_0100096 |
LitCovid-PD-CLO
| Id | Subject | Object | Predicate | Lexical cue |
|---|---|---|---|---|
| T1 | 308-313 | http://purl.obolibrary.org/obo/NCBITaxon_9606 | denotes | human |
LitCovid-PD-CHEBI
| Id | Subject | Object | Predicate | Lexical cue | chebi_id |
|---|---|---|---|---|---|
| T1 | 206-209 | Chemical | denotes | BCG | http://purl.obolibrary.org/obo/CHEBI_41001 |
LitCovid-PubTator
| Id | Subject | Object | Predicate | Lexical cue | tao:has_database_id |
|---|---|---|---|---|---|
| 23 | 308-313 | Species | denotes | human | Tax:9606 |
| 26 | 206-209 | Species | denotes | BCG | Tax:33892 |
| 27 | 24-48 | Disease | denotes | coronavirus disease 2019 | MESH:C000657245 |
| 28 | 50-58 | Disease | denotes | COVID-19 | MESH:C000657245 |
| 29 | 181-189 | Disease | denotes | COVID-19 | MESH:C000657245 |
| 30 | 231-238 | Disease | denotes | malaria | MESH:D008288 |
| 31 | 408-416 | Disease | denotes | COVID-19 | MESH:C000657245 |
| 32 | 594-602 | Disease | denotes | COVID-19 | MESH:C000657245 |
| 33 | 666-674 | Disease | denotes | COVID-19 | MESH:C000657245 |
LitCovid-sentences
| Id | Subject | Object | Predicate | Lexical cue |
|---|---|---|---|---|
| T6 | 93-609 | Sentence | denotes | Here, we evaluated the role of climate (temperature and precipitation), region-specific COVID-19 susceptibility (BCG vaccination factors, malaria incidence, and percentage of the population aged over 65 years), and human mobility (relative amounts of international visitors) in shaping the geographical patterns of COVID-19 case numbers across 1,020 countries/regions, and examined the sequential shift that occurred from December 2019 to June 30, 2020 in multiple drivers of the cumulative number of COVID-19 cases. |