tetano
Editor, Senior Moderator
Environ Res
. 2021 Aug 30;111970.
doi: 10.1016/j.envres.2021.111970. Online ahead of print.
Satellite data and machine learning reveal a significant correlation between NO [SUB]2[/SUB] and COVID-19 mortality
Nicola Amoroso[SUP] 1 [/SUP], Roberto Cilli[SUP] 2 [/SUP], Tommaso Maggipinto[SUP] 3 [/SUP], Alfonso Monaco[SUP] 4 [/SUP], Sabina Tangaro[SUP] 5 [/SUP], Roberto Bellotti[SUP] 3 [/SUP]
Affiliations
Abstract
The Coronavirus disease 2019 (COVID-19) pandemic has officially spread all over the world since the beginning of 2020. Although huge efforts are addressed by scientists to shed light over the several questions raised by the novel SARS-CoV-2 virus, many aspects need to be clarified, yet. In particular, several studies have pointed out significant variations between countries in per-capita mortality. In this work, we investigated the association between COVID-19 mortality with climate variables and air pollution throughout European countries using the satellite remote sensing images provided by the Sentinel-5p mission. We analyzed data collected for two years of observations and extracted the concentrations of several pollutants; we used these measurements to feed a Random Forest regression. We performed a cross-validation analysis to assess the robustness of the model and compared several regression strategies. Our findings reveal a significant statistical association between air pollution (NO[SUB]2[/SUB]) and COVID-19 mortality and a significant role played by the socio-demographic features, like the number of nurses or the hospital beds and the gross domestic product per capita.
Keywords: Covid-19; Pollution; Remote sensing; Sentinel-5p.
. 2021 Aug 30;111970.
doi: 10.1016/j.envres.2021.111970. Online ahead of print.
Satellite data and machine learning reveal a significant correlation between NO [SUB]2[/SUB] and COVID-19 mortality
Nicola Amoroso[SUP] 1 [/SUP], Roberto Cilli[SUP] 2 [/SUP], Tommaso Maggipinto[SUP] 3 [/SUP], Alfonso Monaco[SUP] 4 [/SUP], Sabina Tangaro[SUP] 5 [/SUP], Roberto Bellotti[SUP] 3 [/SUP]
Affiliations
- PMID: 34474031
- DOI: 10.1016/j.envres.2021.111970
Abstract
The Coronavirus disease 2019 (COVID-19) pandemic has officially spread all over the world since the beginning of 2020. Although huge efforts are addressed by scientists to shed light over the several questions raised by the novel SARS-CoV-2 virus, many aspects need to be clarified, yet. In particular, several studies have pointed out significant variations between countries in per-capita mortality. In this work, we investigated the association between COVID-19 mortality with climate variables and air pollution throughout European countries using the satellite remote sensing images provided by the Sentinel-5p mission. We analyzed data collected for two years of observations and extracted the concentrations of several pollutants; we used these measurements to feed a Random Forest regression. We performed a cross-validation analysis to assess the robustness of the model and compared several regression strategies. Our findings reveal a significant statistical association between air pollution (NO[SUB]2[/SUB]) and COVID-19 mortality and a significant role played by the socio-demographic features, like the number of nurses or the hospital beds and the gross domestic product per capita.
Keywords: Covid-19; Pollution; Remote sensing; Sentinel-5p.