| Id |
Subject |
Object |
Predicate |
Lexical cue |
| T249 |
0-204 |
Sentence |
denotes |
Compared to the previous studies, our results are the smallest in magnitude, likely because of the high geographical precision that allows more accurate confounding and spatial autocorrelation adjustment. |
| T250 |
205-326 |
Sentence |
denotes |
In addition, we report weak evidence of an effect, which could also be due to lack of power and individual exposure data. |
| T251 |
327-511 |
Sentence |
denotes |
Nevertheless, as for NO2 we find a high posterior probability of an effect on mortality, we argue that a potential explanation might be the mediation effect of pre-existing conditions. |
| T252 |
512-772 |
Sentence |
denotes |
While in our analysis the inclusion of area-level prevalence of hypertension, diabetes and COPD did not change the results, the ecological nature of the pre-existing conditions data does not allow us to account for the mediation effect at the individual level. |
| T253 |
773-1004 |
Sentence |
denotes |
Our study focuses on the mortality after contracting SARS-CoV-2, however we cannot rule out individual susceptibility to becoming infected as an explanation to the uncertainty in the effect estimates (Villeneuve and Goldberg 2020). |
| T254 |
1005-1124 |
Sentence |
denotes |
Such susceptibility can reflect immunosuppression, leading to later increases in inflammation (Edoardo Conticini et al. |
| T255 |
1125-1279 |
Sentence |
denotes |
2020) and thus worse prognosis, or even disease spread, as recent studies have suggested that PM2.5 can proliferate COVID-19 transmission (Bianconi et al. |
| T256 |
1280-1286 |
Sentence |
denotes |
2020). |
