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. 2020 Nov 4;6(45):eabd4049.
doi: 10.1126/sciadv.abd4049. Print 2020 Nov.

Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis

X Wu  1 , R C Nethery  1 , M B Sabath  1 , D Braun  1   2 , F Dominici  3
Affiliations

Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis

X Wu et al. Sci Adv. .

Abstract

Assessing whether long-term exposure to air pollution increases the severity of COVID-19 health outcomes, including death, is an important public health objective. Limitations in COVID-19 data availability and quality remain obstacles to conducting conclusive studies on this topic. At present, publicly available COVID-19 outcome data for representative populations are available only as area-level counts. Therefore, studies of long-term exposure to air pollution and COVID-19 outcomes using these data must use an ecological regression analysis, which precludes controlling for individual-level COVID-19 risk factors. We describe these challenges in the context of one of the first preliminary investigations of this question in the United States, where we found that higher historical PM2.5 exposures are positively associated with higher county-level COVID-19 mortality rates after accounting for many area-level confounders. Motivated by this study, we lay the groundwork for future research on this important topic, describe the challenges, and outline promising directions and opportunities.

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Figures

Fig. 1
Fig. 1. National maps of historical PM2.5 concentrations and COVID-19 deaths.
Maps show (A) county-level 17-year long-term average of PM2.5 concentrations (2000–2016) in the United States in μg/m3 and (B) county-level number of COVID-19 deaths per 1 million population in the United States up to and including 18 June 2020.
See this image and copyright information in PMC

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