Open AccessINCREASED PM2.5 LEVELS ASSOCIATED WITH INCREASED INCIDENCE OF COVID-19: THE WASHINGTON WILDFIRES OF 2020
Author(s) -
Casey Mace Firebaugh,
Tishra Beeson,
Amie Wojtyna,
Ryan Arboleda
Publication year - 2021
Publication title -
environmental smoke
Language(s) - English
Resource type - Journals
ISSN - 2595-5527
DOI - 10.32435/envsmoke.20214249-53
Subject(s) - covid-19 , incidence (geometry) , confounding , demography , medicine , mortality rate , pandemic , zoology , toxicology , biology , mathematics , geometry , disease , sociology , infectious disease (medical specialty)
Yakima County, Washington was subject to the extrordinary Washington Wildfire Season of 2020 in which unhealty air (PM2.5) persisted for a 14-day period. This remarkable fire and smoke season began in tandem with the COVID-19 pandemic. SARS-CoV-2 virus, like inhaled particulate matter is known to cause respiratory illness or injury. This study sought to determine through publicly available data whether increased levels of PM2.5 were associated with increased cases of COVID-19. Using a 12-day lag analysis, Pearson product correlations were performed between PM2.5 24-hour averages in Yakima County Washington and daily confirmed cases of COVID-19 for data available on March 1, 2020-October 15, 2020. In addition, total running cases of confirmed COVID-19, daily mortality and total running mortality rates were compared in the lag analyses. All days (PM2.5) in the lag analysis were found to have a statistically significant positive correlation with COVID-19 case counts and total running counts of COVID-19 (p<.001) with correlation coefficients ranging from 0.24-0.28. The total running mortality rates were also significantly associated with daily PM2.5 (p<.001); however, the daily mortality rates were not found to be statistically significantly related to PM2.5. This simple analysis provides preliminary evidence that increased air pollution (PM2.5) is associated with higher rates of confirmed COVID-19 cases. However, further research is required to determine the potentially confounding factors in this relationship.