4.7 Article

COVID-19 mortality and exposure to airborne PM2.5: A lag time correlation

Journal

SCIENCE OF THE TOTAL ENVIRONMENT
Volume 806, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scitotenv.2021.151286

Keywords

Correlation analysis; COVID-19; Lag time; Mortality; PM2; 5

Funding

  1. National Natural Science Foundation of China [42075107]
  2. Projects of International Cooperation and Exchanges NSFC [41571130031]
  3. China University of Mining and Technology (Beijing)

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This study investigated the impact of airborne PM2.5 on COVID-19 mortality, revealing that populations exposed to higher levels of PM2.5 pollution are more susceptible to COVID-19 deaths with a lag time of >18 days. Meteorological factors such as temperature and atmospheric pressure were also found to have significant effects on COVID-19 mortality.
COVID-19 has escalated into one of the most serious crises in the 21st Century. Given the rapid spread of SARSCoV-2 and its high mortality rate, here we investigate the impact and relationship of airborne PM2.5 to COVID-19 mortality. Previous studies have indicated that PM2.5 has a positive relationship with the spread of COVID-19. To gain insights into the delayed effect of PM2.5 concentration (mu gm-3) on mortality, we focused on the role of PM2.5 in Wuhan City in China and COVID-19 during the period December 27, 2019 to April 7, 2020. We also considered the possible impact of various meteorological factors such as temperature, precipitation, wind speed, atmospheric pressure and precipitation on pollutant levels. The results from the Pearson's correlation coefficient analyses reveal that the population exposed to higher levels of PM2.5 pollution are susceptible to COVID-19 mortality with a lag time of >18 days. By establishing a generalized additive model, the delayed effect of PM2.5 on the death toll of COVID-19 was verified. A negative correction was identified between temperature and number of COVID19 deaths, whereas atmospheric pressure exhibits a positive correlation with deaths, both with a significant lag effect. The results from our study suggest that these epidemiological relationships may contribute to the understanding of the COVID-19 pandemic and provide insights for public health strategies. Crown Copyright (c) 2021 Published by Elsevier B.V. All rights reserved.

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