Airborne particulate matter, population mobility and COVID-19: a multi-city study in China

Bo Wang, Jiangtao Liu, Yanlin Li, Shihua Fu, Xiaocheng Xu, Lanyu Li, Ji Zhou, Xingrong Liu, Xiaotao He, Jun Yan, Yanjun Shi, Jingping Niu, Yong Yang, Yiyao Li, Bin Luo, Kai Zhang

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Background: Coronavirus disease 2019 (COVID-19) is an emerging infectious disease, which has caused numerous deaths and health problems worldwide. This study aims to examine the effects of airborne particulate matter (PM) pollution and population mobility on COVID-19 across China. Methods: We obtained daily confirmed cases of COVID-19, air particulate matter (PM , PM ), weather parameters such as ambient temperature (AT) and absolute humidity (AH), and population mobility scale index (MSI) in 63 cities of China on a daily basis (excluding Wuhan) from January 01 to March 02, 2020. Then, the Generalized additive models (GAM) with a quasi-Poisson distribution were fitted to estimate the effects of PM , PM and MSI on daily confirmed COVID-19 cases. Results: We found each 1 unit increase in daily MSI was significantly positively associated with daily confirmed cases of COVID-19 in all lag days and the strongest estimated RR (1.21, 95% CIs:1.14 ~ 1.28) was observed at lag 014. In PM analysis, we found each 10 μg/m increase in the concentration of PM and PM was positively associated with the confirmed cases of COVID-19, and the estimated strongest RRs (both at lag 7) were 1.05 (95% CIs: 1.04, 1.07) and 1.06 (95% CIs: 1.04, 1.07), respectively. A similar trend was also found in all cumulative lag periods (from lag 01 to lag 014). The strongest effects for both PM and PM were at lag 014, and the RRs of each 10 μg/m increase were 1.18 (95% CIs:1.14, 1.22) and 1.23 (95% CIs:1.18, 1.29), respectively. Conclusions: Population mobility and airborne particulate matter may be associated with an increased risk of COVID-19 transmission. 2.5 10 10 2.5 10 2.5 10 2.5 3 3
Original languageEnglish
JournalBMC Public Health
Volume20
Issue number1
DOIs
StatePublished - 1 Dec 2020

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