Population-weighted exposure to air pollution and COVID-19 incidence in Germany

Abstract

Many countries have enforced social distancing to stop the spread of COVID-19. Within countries, although the measures taken by governments are similar, the incidence rate varies among areas (e.g., counties, cities). One potential explanation is that people in some areas are more vulnerable to the coronavirus disease because of their worsened health conditions caused by long-term exposure to poor air quality. In this study, we investigate whether long-term exposure to air pollution increases the risk of COVID-19 infection in Germany. The results show that nitrogen dioxide (NO ${}_2$ ) is significantly associated with COVID-19 incidence, with a 1 $\mu g$ m ${}^{-3}$ increase in long-term exposure to NO ${}_2$ increasing the COVID-19 incidence rate by 5.58% (95% credible interval [CI]: 3.35%, 7.86%). This result is consistent across various models. The analyses can be reproduced and updated routinely using public data sources and shared R code.

Keywords: Air pollution; COVID-19; Health impacts; INLA; Kriging.

Fig. 1

Pollution stations, population density, log of COVID-19 SIR and population-weighted NO${}_2$ ($\mathrm{\mu }$g m${}^{-3}$) by county in Germany.

Fig. 2

Upper: scatterplots of log COVID-19 SIR against NO${}_2$ ($\mathrm{\mu }$g m${}^{-3}$) and PM_2.5 ($\mathrm{\mu }$g m${}^{-3}$); Middle: the Moran’s I test and the empirical semi-variogram of the residuals from the non-spatial health model (circles), with 95% Monte Carlo simulation envelopes (dashed lines); Bottom: posterior (solid line) and prior (dashed line) plots for $\xi$ and $\kappa$ from health model (8).

Fig. 3

Posterior means of relative risk E$\left({\lambda }_k\right|Y)$ and probabilities of 50% excess risk Pr$(exp\left({\varphi }_i\right)>1.5\mid Y)$.