Quantifying the impact of air pollution on Covid-19 hospitalisation and death rates in Scotland.

Duncan Lee, Chris Robertson, Carole McRae, Jessica Baker
Author Information
  1. Duncan Lee: School of Mathematics and Statistics, University of Glasgow, Glasgow, G12 8SQ, Scotland, United Kingdom. Electronic address: Duncan.Lee@glasgow.ac.uk.
  2. Chris Robertson: Department of Mathematics and Statistics, University of Strathclyde, Glasgow, G1 1XH, Scotland, United Kingdom; Public Health Scotland, Meridian Court, 5 Cadogan Street, Glasgow G2 6QE, Scotland, United Kingdom. Electronic address: chris.robertson@strath.ac.uk.
  3. Carole McRae: Public Health Scotland, Meridian Court, 5 Cadogan Street, Glasgow G2 6QE, Scotland, United Kingdom. Electronic address: carole.mcrae@phs.scot.
  4. Jessica Baker: Public Health Scotland, Meridian Court, 5 Cadogan Street, Glasgow G2 6QE, Scotland, United Kingdom. Electronic address: jessica.baker2@phs.scot.

Abstract

Better understanding the risk factors that exacerbate Covid-19 symptoms and lead to worse health outcomes is vitally important in the public health fight against the virus. One such risk factor that is currently under investigation is air pollution concentrations, with some studies finding statistically significant effects while other studies have found no consistent associations. The aim of this paper is to add to this global evidence base on the potential association between air pollution concentrations and Covid-19 hospitalisations and deaths, by presenting the first study on this topic at the small-area scale in Scotland, United Kingdom. Our study is one of the most comprehensive to date in terms of its temporal coverage, as it includes all hospitalisations and deaths in Scotland between 1st March 2020 and 31st July 2021. We quantify the effects of air pollution on Covid-19 outcomes using a small-area spatial ecological study design, with inference using Bayesian hierarchical models that allow for the residual spatial correlation present in the data. A key advantage of our study is its extensive sensitivity analyses, which examines the robustness of the results to our modelling assumptions. We find clear evidence that PM concentrations are associated with hospital admissions, with a 1 μgm increase in concentrations being associated with between a 7.4% and a 9.3% increase in hospitalisations. In addition, we find some evidence that PM concentrations are associated with deaths, with a 1 μgm increase in concentrations being associated with between a 2.9% and a 10.3% increase in deaths.

Keywords

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MeSH Term

Air Pollutants
Air Pollution
Bayes Theorem
COVID-19
Hospitalization
Humans
Particulate Matter

Chemicals

Air Pollutants
Particulate Matter

Word Cloud

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