Project at a Glance

Title: Impact of Air Pollution on COVID-19 Case and Death Risk in California

Principal Investigator / Author(s): Reynolds, Peggy

Contractor: UC San Francisco

Contract Number: 19RD029


Research Program Area: Health & Exposure

Topic Areas: Health Effects of Air Pollution


Research Summary:

Long-term exposure to air pollution is emerging as one of the most important risk factors for deaths from coronavirus disease 2019 (COVID-19) infections. A preliminary study from Harvard has shown that an increase in 1 µg/m3 in PM2.5 was related to an 8 percent increase in COVID-19 death rates in the U.S. The Harvard study, while helpful in introducing the concern of a linkage between air pollution and COVID-19, needs to be repeated in California with more specific data at a smaller scale. Given the high levels of pollution in California and the concern for community and individual exposure to air pollution, this study is critical to be able to determine the vulnerability of Californians to COVID-19. Using more spatially refined data on case/death counts and exposure estimates, the investigators propose to study the relationship of several air pollutants: PM2.5, PM10, NO2 and O3, with COVID-19 case/death rates in California. The University of California, San Francisco (UCSF) will focus not only on long-term exposures, but also more proximal exposures before the COVID-19 outbreak. UCSF will also be able to examine the risk of more severe cases of COVID-19 using hospitalization and Intensive Care Unit (ICU) counts, and also focus specifically on the impact of COVID-19 on EJ and vulnerable communities in California. After obtaining exposure estimates and address-level COVID-19 data, the investigators will assemble an analysis dataset in a GIS platform, which will link health and exposure data with other important covariates. Covariate datasets will include the American Community Survey (ACS), the Behavioral Risk Factor Surveillance System (BRFSS), CalEnviroScreen, U.S. Census, and other data as needed. Areas will be adjusted for testing rates as possible. Multivariable and mixed statistical models will be performed on the data as appropriate to estimate COVID-19 risk. The sensitivity of the results to additions/removals of key covariates will be examined. A final report and metadata will be provided to CARB upon completion.


For questions regarding this research project, including available data and progress status, contact: Research Division staff at (916) 445-0753

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