Risk of COVID-19 and long-term exposure to air pollution: evidence from the first wave in China

Abstract

AbstractPeople with chronic obstructive pulmonary disease, cardiovascular disease or hypertension have a high risk of severe coronavirus disease 2019 (COVID-19). Long-term exposure to air pollution, especially PM2.5, has also been associated with COVID-19 mortality. We collated individual-level data of confirmed COVID-19 cases during the first wave of the epidemic in mainland China. We fitted a generalized linear model using city-level COVID-19 cases and severe cases as the outcome, and long-term average levels of air pollutants as the exposure. Our analysis was adjusted using several variables, including a mobile phone dataset, covering human movement from Wuhan before the travel ban and movements within each city during the time of emergency response. Other variables included census, smoking prevalence, climate, and socio-economic data from 324 cities in China. We adjusted for human mobility and socio-economic factors, and found that an increase in long-term NO2 or PM2.5 may correspond to an increase in the number of COVID-19 cases and severe infections. However, the linkage might also be affected by the confounding factor of population size because of the predefined correlation between population size and air pollution. The results are derived from a large, newly compiled and geocoded repository of population and epidemiological data relevant to COVID-19. The findings of this paper (and other previous studies that have given ambiguous results) indicate that a more definitive analysis is needed of the link between COVID-19 and air pollution.