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A Spatiotemporal Analytical Outlook of the Exposure to Air Pollution and COVID-19 Mortality in the USA

Author

Listed:
  • Sounak Chakraborty

    (University of Missouri)

  • Tanujit Dey

    (Brigham and Women’s Hospital, Harvard Medical School)

  • Yoonbae Jun

    (Seoul National University)

  • Chae Young Lim

    (Seoul National University)

  • Anish Mukherjee

    (University of Louisville)

  • Francesca Dominici

    (Harvard T.H. Chan School of Public Health)

Abstract

The world is experiencing a pandemic due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), also known as COVID-19. The USA is also suffering from a catastrophic death toll from COVID-19. Several studies are providing preliminary evidence that short- and long-term exposure to air pollution might increase the severity of COVID-19 outcomes, including a higher risk of death. In this study, we develop a spatiotemporal model to estimate the association between exposure to fine particulate matter PM2.5 and mortality accounting for several social and environmental factors. More specifically, we implement a Bayesian zero-inflated negative binomial regression model with random effects that vary in time and space. Our goal is to estimate the association between air pollution and mortality accounting for the spatiotemporal variability that remained unexplained by the measured confounders. We applied our model to four regions of the USA with weekly data available for each county within each region. We analyze the data separately for each region because each region shows a different disease spread pattern. We found a positive association between long-term exposure to PM2.5 and the mortality from the COVID-19 disease for all four regions with three of four being statistically significant. Data and code are available at our GitHub repository. Supplementary materials accompanying this paper appear on-line.

Suggested Citation

  • Sounak Chakraborty & Tanujit Dey & Yoonbae Jun & Chae Young Lim & Anish Mukherjee & Francesca Dominici, 2022. "A Spatiotemporal Analytical Outlook of the Exposure to Air Pollution and COVID-19 Mortality in the USA," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(3), pages 419-439, September.
    • Handle: RePEc:spr:jagbes:v:27:y:2022:i:3:d:10.1007_s13253-022-00487-1
    DOI: 10.1007/s13253-022-00487-1
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    References listed on IDEAS

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    1. Silvia Comunian & Dario Dongo & Chiara Milani & Paola Palestini, 2020. "Air Pollution and COVID-19: The Role of Particulate Matter in the Spread and Increase of COVID-19’s Morbidity and Mortality," IJERPH, MDPI, vol. 17(12), pages 1-22, June.
    2. Nicholas G. Polson & James G. Scott & Jesse Windle, 2013. "Bayesian Inference for Logistic Models Using Pólya--Gamma Latent Variables," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(504), pages 1339-1349, December.
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