On the lagged non-linear association between air pollution and COVID-19 cases in Belgium

Abstract

Exposure to air pollution has been proposed as a determinant of COVID-19 dynamics. While the connection between air pollution and COVID-19 has been established for several countries worldwide, few such analyses exist in Belgium. Therefore, we examine this potential association in Belgium, using COVID-19 cases of all 581 municipalities between September 2020 and January 2022. We employ a Bayesian spatio-temporal negative binomial model, allowing for potential non-linear and lagged effects of pollution. Comparing different single-pollutant models, we find that the model providing the best fit to the data contains black carbon. At the median pollution level, a cumulative risk of $1.66(1.57,1.74)$ over 8 weeks is found for this pollutant, compared to the 5% pollution quantile. In addition, the study reveals a remarkable similarity in COVID-19 incidence between adjacent municipalities in Belgium.

Our findings suggest paying careful attention to highly air polluted areas when preparing for future pandemics of respiratory diseases.