Abstract
Exposure to particulate matter (PM) could increase both susceptibility to SARS-CoV-2 infection and severity of COVID-19 disease. Prior studies investigating associations between PM and COVID-19 morbidity have only considered PM2.5 or PM10, rather than PM1. We investigated the associations between daily-diagnosed COVID-19 morbidity and average exposures to ambient PM1 starting at 0 through 21 days before the day of diagnosis in 12 cities in China using a two-step analysis: a time-series quasi-Poisson analysis to analyze the associations in each city; and then a meta-analysis to estimate the overall association. Diagnosed morbidities and PM1 data were obtained from National Health Commission in China and China Meteorological Administration, respectively. We found association between short-term exposures to ambient PM1 with COVID-19 morbidity was significantly positive, and larger than the associations with PM2.5 and PM10. Percent increases in daily-diagnosed COVID-19 morbidity per IQR/10 PM1 for different moving averages ranged from 1.50% (−1.20%, 4.30%) to 241% (95%CI: 80.7%, 545%), with largest values for exposure windows starting at 17 days before diagnosis. Our results indicate that smaller particles are more highly associated with COVID-19 morbidity, and most of the effects from PM2.5 and PM10 on COVID-19 may be primarily due to the PM1. This study will be helpful for implementing measures and policies to control the spread of COVID-19.
Original language | English |
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Article number | 113016 |
Journal | Environmental Research |
Volume | 210 |
DOIs | |
Publication status | Published - Jul 2022 |
Keywords
- COVID-19
- China
- PM
- Time-serial analysis