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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
326 1369-1375 Species denotes people Tax:9606
327 558-568 Disease denotes infections MESH:D007239
328 606-616 Disease denotes infections MESH:D007239
329 681-689 Disease denotes COVID-19 MESH:C000657245
330 854-860 Disease denotes deaths MESH:D003643
331 938-944 Disease denotes deaths MESH:D003643
332 1335-1341 Disease denotes deaths MESH:D003643
333 1646-1654 Disease denotes COVID-19 MESH:C000657245
334 1830-1838 Disease denotes COVID-19 MESH:C000657245
335 1839-1848 Disease denotes mortality MESH:D003643

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T235 0-36 Sentence denotes Our study has also some limitations.
T236 37-115 Sentence denotes The downscaling procedure will likely inflate the reported credible intervals.
T237 116-230 Sentence denotes However, this naturally reflects the uncertainty of the place of residence resulted from the downscaling approach.
T238 231-388 Sentence denotes Although we consider small areas, the study is still an ecological one and thus the reported effects do not reflect individual associations (Wakefield 2008).
T239 389-520 Sentence denotes Case fatality might have been a more appropriate metric for the analysis, since disease spread is accounted for in the denominator.
T240 521-735 Sentence denotes Nevertheless, given the asymptomatic infections and the fact that number of reported infections is not a random sample of the general population, the number of COVID-19 cases per LTLA is not reliable at this stage.
T241 736-945 Sentence denotes For the same reason, using the number of reported cases to adjust for disease progression and clustering of cases and deaths might not adequately capture disease progression and clustering of cases and deaths.
T242 946-1028 Sentence denotes However, part of this clustering was captured in the spatial autocorrelation term.
T243 1029-1165 Sentence denotes We did not account for population mobility during 2014–2018 and assumed constant residence and thus levels of exposure to air-pollution.
T244 1166-1427 Sentence denotes While this is a limitation, we believe that it would have a minimal impact on the results given that 1) the exposure period is relatively short and 2) almost 93% of the deaths in our dataset occurred in people 60 years or older (Supplemental Material Table S2).
T245 1428-1532 Sentence denotes This comprises a population less likely to have moved during the past 5 years (Burgess and Quinio 2020).
T246 1533-1602 Sentence denotes We also could not account for non-residential air-pollution exposure.
T247 1603-1867 Sentence denotes Spatiotemporal variation in the strains of COVID-19 can introduce bias (Villeneuve and Goldberg 2020), however at the time of publication there was no evidence supporting that strain types can confound the relationship between COVID-19 mortality and air-pollution.