COVID-19 and air pollution in Vienna—a time series approach. Moshammer, H., Poteser, M., & Hutter, H. Wiener klinische Wochenschrift, May, 2021. ![COVID-19 and air pollution in Vienna—a time series approach [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Summary We performed a time series analysis in Vienna, Austria, investigating the temporal association between daily air pollution (nitrogen dioxide, NO 2 and particulate matter smaller than 10 µm, PM10) concentration and risk of coronavirus disease 2019 (COVID-19) infection and death. Data covering about 2 months (March–April 2020) were retrieved from public databases. Infection risk was defined as the ratio between infected and infectious. In a separate sensitivity analysis different models were applied to estimate the number of infectious people per day. The impact of air pollution was assessed through a linear regression on the natural logarithm of infection risk. Risk of COVID-19 mortality was estimated by Poisson regression. Both pollutants were positively correlated with the risk of infection with the coefficient for NO 2 being 0.032 and for PM10 0.014. That association was significant for the irritant gas ( p = 0.012) but not for particles ( p = 0.22). Pollutants did not affect COVID-19-related mortality. The study findings might have wider implications on an interaction between air pollution and infectious agents.
@article{moshammer_covid-19_2021,
title = {{COVID}-19 and air pollution in {Vienna}—a time series approach},
issn = {0043-5325, 1613-7671},
url = {https://link.springer.com/10.1007/s00508-021-01881-4},
doi = {10.1007/s00508-021-01881-4},
abstract = {Summary
We performed a time series analysis in Vienna, Austria, investigating the temporal association between daily air pollution (nitrogen dioxide, NO
2
and particulate matter smaller than 10 µm, PM10) concentration and risk of coronavirus disease 2019 (COVID-19) infection and death. Data covering about 2 months (March–April 2020) were retrieved from public databases. Infection risk was defined as the ratio between infected and infectious. In a separate sensitivity analysis different models were applied to estimate the number of infectious people per day. The impact of air pollution was assessed through a linear regression on the natural logarithm of infection risk. Risk of COVID-19 mortality was estimated by Poisson regression. Both pollutants were positively correlated with the risk of infection with the coefficient for NO
2
being 0.032 and for PM10 0.014. That association was significant for the irritant gas (
p
= 0.012) but not for particles (
p
= 0.22). Pollutants did not affect COVID-19-related mortality. The study findings might have wider implications on an interaction between air pollution and infectious agents.},
language = {en},
urldate = {2021-05-14},
journal = {Wiener klinische Wochenschrift},
author = {Moshammer, Hanns and Poteser, Michael and Hutter, Hans-Peter},
month = may,
year = {2021},
pmcid = {PMC8101341},
pmid = {33959810},
keywords = {COVID-19},
}
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