Long-term exposure to air-pollution and COVID-19 mortality in England: a hierarchical spatial analysis

ABSTRACT

BackgroundRecent studies suggested a link between long-term exposure to air-pollution and COVID-19 mortality. However, due to their ecological design, based on large spatial units, they neglect the strong localised air-pollution patterns, and potentially lead to inadequate confounding adjustment. We investigated the effect of long-term exposure to NO2 and PM2{middle dot}5 on COVID-19 deaths up to June 30, 2020 in England using high geographical resolution. Methods We included 38 573 COVID-19 deaths up to June 30, 2020 at the Lower Layer Super Output Area level in England (n=32 844 small areas). We retrieved averaged NO2 and PM2{middle dot}5 concentration during 2014-2018 from the Pollution Climate Mapping. We used Bayesian hierarchical models to quantify the effect of air-pollution while adjusting for a series of confounding and spatial autocorrelation. FindingsWe find a 0{middle dot}5% (95% credible interval -0{middle dot}2%-1{middle dot}2%) and 1{middle dot}4% (-2{middle dot}1%-5{middle dot}1%) increase in COVID-19 mortality rate for every 1g/m3 increase in NO2 and PM2{middle dot}5 respectively, after adjusting for confounding and spatial autocorrelation. This corresponds to a posterior probability of a positive effect of 0{middle dot}93 and 0{middle dot}78 respectively. The spatial relative risk at LSOA level revealed strong patterns, similar for the different pollutants. This potentially captures the spread of the disease during the first wave of the epidemic. InterpretationOur study provides some evidence of an effect of long-term NO2 exposure on COVID-19 mortality, while the effect of PM2{middle dot}5 remains more uncertain. FundingMedical Research Council, Wellcome Trust, Environmental Protection Agency and National Institutes of Health.