PMC:7589163 / 42455-43788
Annnotations
LitCovid-PD-MONDO
| Id | Subject | Object | Predicate | Lexical cue | mondo_id |
|---|---|---|---|---|---|
| T169 | 42-50 | Disease | denotes | COVID-19 | http://purl.obolibrary.org/obo/MONDO_0100096 |
| T170 | 132-142 | Disease | denotes | infections | http://purl.obolibrary.org/obo/MONDO_0005550 |
| T171 | 621-629 | Disease | denotes | COVID-19 | http://purl.obolibrary.org/obo/MONDO_0100096 |
| T172 | 795-803 | Disease | denotes | COVID-19 | http://purl.obolibrary.org/obo/MONDO_0100096 |
| T173 | 1209-1217 | Disease | denotes | COVID-19 | http://purl.obolibrary.org/obo/MONDO_0100096 |
LitCovid-PD-CLO
| Id | Subject | Object | Predicate | Lexical cue |
|---|---|---|---|---|
| T442 | 60-63 | http://purl.obolibrary.org/obo/CLO_0051582 | denotes | has |
| T443 | 111-113 | http://purl.obolibrary.org/obo/CLO_0053733 | denotes | 11 |
| T444 | 399-404 | http://purl.obolibrary.org/obo/NCBITaxon_10239 | denotes | virus |
| T445 | 595-596 | http://purl.obolibrary.org/obo/CLO_0001020 | denotes | A |
| T446 | 643-646 | http://purl.obolibrary.org/obo/CLO_0051582 | denotes | has |
| T447 | 687-688 | http://purl.obolibrary.org/obo/CLO_0001020 | denotes | a |
| T448 | 1000-1001 | http://purl.obolibrary.org/obo/CLO_0001020 | denotes | a |
| T449 | 1073-1074 | http://purl.obolibrary.org/obo/CLO_0001020 | denotes | a |
LitCovid-sentences
| Id | Subject | Object | Predicate | Lexical cue |
|---|---|---|---|---|
| T256 | 0-143 | Sentence | denotes | At the time of writing (3 July 2020), the COVID-19 pandemic has claimed over 500,000 lives worldwide with over 11 million confirmed infections. |
| T257 | 144-301 | Sentence | denotes | Different regions of the world have been differently affected by the pandemic, with Northern Italy setting an unfortunate record for incidence and mortality. |
| T258 | 302-594 | Sentence | denotes | Different factors might explain these geographical variations, such as the earlier spread of the virus in certain countries or the different preventive measures adopted, the different climates and air-pollution levels, or the different age-composition and social proximity of the communities. |
| T259 | 595-674 | Sentence | denotes | A North–South gradient in COVID-19 distribution has been noticed [174,175,176]. |
| T260 | 675-810 | Sentence | denotes | Areas along a latitude of 30–50° N with similar low-humidity, temperate weather, showed significant community spread of COVID-19 [177]. |
| T261 | 811-961 | Sentence | denotes | Marik and colleagues calculated the case-fatality rate in each state of the US and found increasing mortality with increasing latitude (>40° N) [178]. |
| T262 | 962-1116 | Sentence | denotes | More recently, another study reported a highly significant, positive correlation between lower death rates and a country’s proximity to the equator [179]. |
| T263 | 1117-1333 | Sentence | denotes | Rhodes et al. described that more northerly countries are currently showing relatively high COVID-19 mortality, with an estimated 4.4% increase in mortality for each 1-degree latitude north of 28 degrees North [180]. |
LitCovid-PubTator
| Id | Subject | Object | Predicate | Lexical cue | tao:has_database_id |
|---|---|---|---|---|---|
| 1094 | 42-50 | Disease | denotes | COVID-19 | MESH:C000657245 |
| 1095 | 132-142 | Disease | denotes | infections | MESH:D007239 |
| 1096 | 291-300 | Disease | denotes | mortality | MESH:D003643 |
| 1097 | 621-629 | Disease | denotes | COVID-19 | MESH:C000657245 |
| 1098 | 795-803 | Disease | denotes | COVID-19 | MESH:C000657245 |
| 1099 | 911-920 | Disease | denotes | mortality | MESH:D003643 |
| 1100 | 1057-1062 | Disease | denotes | death | MESH:D003643 |
| 1101 | 1209-1217 | Disease | denotes | COVID-19 | MESH:C000657245 |
| 1102 | 1218-1227 | Disease | denotes | mortality | MESH:D003643 |
| 1103 | 1264-1273 | Disease | denotes | mortality | MESH:D003643 |