| Id |
Subject |
Object |
Predicate |
Lexical cue |
| T32 |
0-253 |
Sentence |
denotes |
Previous studies suggested an effect of long-term exposure to air-pollution on COVID-19 mortality (Cole et al., 2020, Liang et al., 2020, Travaglio et al., 2020, Wu et al., 2020), however several methodological shortcomings limit their interpretability. |
| T33 |
254-429 |
Sentence |
denotes |
They were based on data aggregated on large spatial units and thus suffer from ecological fallacy (grouped levels association do not reflect individual ones) (Wakefield 2008). |
| T34 |
430-607 |
Sentence |
denotes |
Air pollution is characterised by high spatial variability, making the availability of mortality data at the same high spatial resolution crucial (Villeneuve and Goldberg 2020). |
| T35 |
608-784 |
Sentence |
denotes |
In addition, a coarse geographical resolution might lead to inadequate adjustment for confounders, when these are available at higher resolution (Villeneuve and Goldberg 2020). |
| T36 |
785-1016 |
Sentence |
denotes |
Most previous studies assessed cumulative deaths until mid or end of April and thus the generalisability of their results is limited to the early stages of the epidemic (Liang et al., 2020, Travaglio et al., 2020, Wu et al., 2020). |
| T37 |
1017-1077 |
Sentence |
denotes |
One study had data available up to June 5, 2020 (Cole et al. |
| T38 |
1078-1205 |
Sentence |
denotes |
2020) and another up to June 12, 2020 (Statistics 2020), capturing a proportion COVID-19 deaths attributable to the first wave. |
