Airborne particulate matter, population mobility and COVID-19: a multi-city study in China
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RESEARCH ARTICLE
Open Access
Airborne particulate matter, population mobility and COVID-19: a multi-city study in China Bo Wang1†, Jiangtao Liu1†, Yanlin Li1, Shihua Fu1, Xiaocheng Xu1, Lanyu Li1, Ji Zhou2, Xingrong Liu1, Xiaotao He1, Jun Yan3, Yanjun Shi4, Jingping Niu1, Yong Yang5, Yiyao Li6, Bin Luo1,2,7* and Kai Zhang8,9
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 (PM2.5, PM10), 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 PM10, PM2.5 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/m3 increase in the concentration of PM10 and PM2.5 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 PM10 and PM2.5 were at lag 014, and the RRs of each 10 μg/m3 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. Keywords: COVID-19, Particulate matter, Population mobility, Generalized additive models
* Correspondence: [email protected] † Bo Wang and Jiangtao Liu contributed equally to this work. 1 Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu 730000, People’s Republic of China 2 Shanghai Key Laboratory of Meteorology and Health, Shanghai Meteorological Bureau, Shanghai 200030, People’s Republic of China Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in
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