Combining aggregate and individual-level data to estimate individual-level associations between air pollution and COVID-19 mortality in the United States

Author:

Woodward Sophie M.ORCID,Mork DanielORCID,Wu XiaoORCID,Hou Zhewen,Braun DanielleORCID,Dominici Francesca

Abstract

Imposing stricter regulations for PM2.5 has the potential to mitigate damaging health and climate change effects. Recent evidence establishing a link between exposure to air pollution and COVID-19 outcomes is one of many arguments for the need to reduce the National Ambient Air Quality Standards (NAAQS) for PM2.5. However, many studies reporting a relationship between COVID-19 outcomes and PM2.5 have been criticized because they are based on ecological regression analyses, where area-level counts of COVID-19 outcomes are regressed on area-level exposure to air pollution and other covariates. It is well known that regression models solely based on area-level data are subject to ecological bias, i.e., they may provide a biased estimate of the association at the individual-level, due to within-area variability of the data. In this paper, we augment county-level COVID-19 mortality data with a nationally representative sample of individual-level covariate information from the American Community Survey along with high-resolution estimates of PM2.5 concentrations obtained from a validated model and aggregated to the census tract for the contiguous United States. We apply a Bayesian hierarchical modeling approach to combine county-, census tract-, and individual-level data to ultimately draw inference about individual-level associations between long-term exposure to PM2.5 and mortality for COVID-19. By analyzing data prior to the Emergency Use Authorization for the COVID-19 vaccines we found that an increase of 1 μg/m3 in long-term PM2.5 exposure, averaged over the 17-year period 2000-2016, is associated with a 3.3% (95% credible interval, 2.8 to 3.8%) increase in an individual’s odds of COVID-19 mortality. Code to reproduce our study is publicly available at https://github.com/NSAPH/PM_COVID_ecoinference. The results confirm previous evidence of an association between long-term exposure to PM2.5 and COVID-19 mortality and strengthen the case for tighter regulations on harmful air pollution and greenhouse gas emissions.

Funder

Health Effects Institute

U.S. Environmental Protection Agency

Climate Change Solutions Fund

2020 Harvard Star-Friedman Award for Promising Scientific Research

NIH

Harvard University

Fernholz Foundation

Publisher

Public Library of Science (PLoS)

Reference90 articles.

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3. US Environmental Protection Agency. Reviewing National Ambient Air Quality Standards (NAAQS): Scientific and Technical Information. EPA. 2021; EPA–HQ–OAR–2015–0072.

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