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Association between Long-Term PM2.5 Exposure and COVID-19 Spread in the United States
PAI LIU, Payton Beeler, Rajan K. Chakrabarty, Washington University in St. Louis
Abstract Number: 556
Working Group: The Role of Aerosol Science in the Understanding of the Spread and Control of COVID-19 and Other Infectious Diseases
Abstract
The rampage of coronavirus disease 2019 (COVID-19) epidemic has spread across the United States (US) and killed more than a-hundred-thousand people. Latest epidemiology studies have identified long-term exposure to air pollution as a significant contributor to the COVID-19 mortality. However, the influence of various PM2.5 composition on COVID-19 progression – an essential information necessary for enforcing effective air pollution regulations – remains an unknown research question. Here we discuss the results on a statistical analysis investigating the relationship between the PM2.5 chemical composition and COVID-19 progression rate in the continental US between March 2 and April 29, 2020, during which the country was under the stay-at-home order. We collected state-level long-term (between 2000 and 2017) PM2.5 composition dataset produced by Van Donekelaar et al. (2019). This dataset is a fusion of three different sources: ground-based monitors, GEOS-CHEM model, and satellite observations. The derived PM2.5 composition data is next correlated with the corresponding state-wise basic reproduction ratio (R0) values of COVID-19, which were inferred from the time-evolution of epidemic size (between March 2 and April 29, 2020) with the well-established susceptible-exposed-infected-removed model. This presentation discusses a significant positive correlation between the PM2.5 composition and the R0 values of COVID-19.