tetano
Editor, Senior Moderator
Sci Rep
. 2021 Apr 16;11(1):8363.
doi: 10.1038/s41598-021-87877-6.
Highlighting the compound risk of COVID-19 and environmental pollutants using geospatial technology
Ram Kumar Singh[SUP] 1 [/SUP], Martin Drews[SUP] 2 [/SUP], Manuel De la Sen[SUP] 3 [/SUP], Prashant Kumar Srivastava[SUP] 4 5 [/SUP], Bambang H Trisasongko[SUP] 6 [/SUP], Manoj Kumar[SUP] 7 [/SUP], Manish Kumar Pandey[SUP] 4 [/SUP], Akash Anand[SUP] 4 [/SUP], S S Singh[SUP] 8 [/SUP], A K Pandey[SUP] 9 [/SUP], Manmohan Dobriyal[SUP] 9 [/SUP], Meenu Rani[SUP] 10 [/SUP], Pavan Kumar[SUP] 11 [/SUP]
Affiliations
Abstract
The new COVID-19 coronavirus disease has emerged as a global threat and not just to human health but also the global economy. Due to the pandemic, most countries affected have therefore imposed periods of full or partial lockdowns to restrict community transmission. This has had the welcome but unexpected side effect that existing levels of atmospheric pollutants, particularly in cities, have temporarily declined. As found by several authors, air quality can inherently exacerbate the risks linked to respiratory diseases, including COVID-19. In this study, we explore patterns of air pollution for ten of the most affected countries in the world, in the context of the 2020 development of the COVID-19 pandemic. We find that the concentrations of some of the principal atmospheric pollutants were temporarily reduced during the extensive lockdowns in the spring. Secondly, we show that the seasonality of the atmospheric pollutants is not significantly affected by these temporary changes, indicating that observed variations in COVID-19 conditions are likely to be linked to air quality. On this background, we confirm that air pollution may be a good predictor for the local and national severity of COVID-19 infections.
. 2021 Apr 16;11(1):8363.
doi: 10.1038/s41598-021-87877-6.
Highlighting the compound risk of COVID-19 and environmental pollutants using geospatial technology
Ram Kumar Singh[SUP] 1 [/SUP], Martin Drews[SUP] 2 [/SUP], Manuel De la Sen[SUP] 3 [/SUP], Prashant Kumar Srivastava[SUP] 4 5 [/SUP], Bambang H Trisasongko[SUP] 6 [/SUP], Manoj Kumar[SUP] 7 [/SUP], Manish Kumar Pandey[SUP] 4 [/SUP], Akash Anand[SUP] 4 [/SUP], S S Singh[SUP] 8 [/SUP], A K Pandey[SUP] 9 [/SUP], Manmohan Dobriyal[SUP] 9 [/SUP], Meenu Rani[SUP] 10 [/SUP], Pavan Kumar[SUP] 11 [/SUP]
Affiliations
- PMID: 33863975
- DOI: 10.1038/s41598-021-87877-6
Abstract
The new COVID-19 coronavirus disease has emerged as a global threat and not just to human health but also the global economy. Due to the pandemic, most countries affected have therefore imposed periods of full or partial lockdowns to restrict community transmission. This has had the welcome but unexpected side effect that existing levels of atmospheric pollutants, particularly in cities, have temporarily declined. As found by several authors, air quality can inherently exacerbate the risks linked to respiratory diseases, including COVID-19. In this study, we explore patterns of air pollution for ten of the most affected countries in the world, in the context of the 2020 development of the COVID-19 pandemic. We find that the concentrations of some of the principal atmospheric pollutants were temporarily reduced during the extensive lockdowns in the spring. Secondly, we show that the seasonality of the atmospheric pollutants is not significantly affected by these temporary changes, indicating that observed variations in COVID-19 conditions are likely to be linked to air quality. On this background, we confirm that air pollution may be a good predictor for the local and national severity of COVID-19 infections.