Outdoor PM2.5 concentration and rate of change in COVID-19 infection in provincial capital cities in China

Abstract This study investigates thoroughly whether acute exposure to outdoor PM2.5 concentration, P, modifies the rate of change in the daily number of COVID-19 infections (R) across 18 high infection provincial capitals in China, including Wuhan. A best-fit multiple linear regression model was con...

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Autores principales:	Yang Han, Jacqueline C. K. Lam, Victor O. K. Li, Jon Crowcroft, Jinqi Fu, Jocelyn Downey, Illana Gozes, Qi Zhang, Shanshan Wang, Zafar Gilani
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/816e12d7d07f4da695dae48ab68dc4a0
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spelling	oai:doaj.org-article:816e12d7d07f4da695dae48ab68dc4a02021-12-05T12:15:34ZOutdoor PM2.5 concentration and rate of change in COVID-19 infection in provincial capital cities in China10.1038/s41598-021-02523-52045-2322https://doaj.org/article/816e12d7d07f4da695dae48ab68dc4a02021-12-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-02523-5https://doaj.org/toc/2045-2322Abstract This study investigates thoroughly whether acute exposure to outdoor PM2.5 concentration, P, modifies the rate of change in the daily number of COVID-19 infections (R) across 18 high infection provincial capitals in China, including Wuhan. A best-fit multiple linear regression model was constructed to model the relationship between P and R, from 1 January to 20 March 2020, after accounting for meteorology, net move-in mobility (NM), time trend (T), co-morbidity (CM), and the time-lag effects. Regression analysis shows that P (β = 0.4309, p < 0.001) is the most significant determinant of R. In addition, T (β = −0.3870, p < 0.001), absolute humidity (AH) (β = 0.2476, p = 0.002), P × AH (β = −0.2237, p < 0.001), and NM (β = 0.1383, p = 0.003) are more significant determinants of R, as compared to GDP per capita (β = 0.1115, p = 0.015) and CM (Asthma) (β = 0.1273, p = 0.005). A matching technique was adopted to demonstrate a possible causal relationship between P and R across 18 provincial capital cities. A 10 µg/m3 increase in P gives a 1.5% increase in R (p < 0.001). Interaction analysis also reveals that P × AH and R are negatively correlated (β = −0.2237, p < 0.001). Given that P exacerbates R, we recommend the installation of air purifiers and improved air ventilation to reduce the effect of P on R. Given the increasing observation that COVID-19 is airborne, measures that reduce P, plus mandatory masking that reduces the risks of COVID-19 associated with viral-particulate transmission, are strongly recommended. Our study is distinguished by the focus on the rate of change instead of the individual cases of COVID-19 when modelling the statistical relationship between R and P in China; causal instead of correlation analysis via the matching analysis, while taking into account the key confounders, and the individual plus the interaction effects of P and AH on R.Yang HanJacqueline C. K. LamVictor O. K. LiJon CrowcroftJinqi FuJocelyn DowneyIllana GozesQi ZhangShanshan WangZafar GilaniNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yang Han Jacqueline C. K. Lam Victor O. K. Li Jon Crowcroft Jinqi Fu Jocelyn Downey Illana Gozes Qi Zhang Shanshan Wang Zafar Gilani Outdoor PM2.5 concentration and rate of change in COVID-19 infection in provincial capital cities in China
description	Abstract This study investigates thoroughly whether acute exposure to outdoor PM2.5 concentration, P, modifies the rate of change in the daily number of COVID-19 infections (R) across 18 high infection provincial capitals in China, including Wuhan. A best-fit multiple linear regression model was constructed to model the relationship between P and R, from 1 January to 20 March 2020, after accounting for meteorology, net move-in mobility (NM), time trend (T), co-morbidity (CM), and the time-lag effects. Regression analysis shows that P (β = 0.4309, p < 0.001) is the most significant determinant of R. In addition, T (β = −0.3870, p < 0.001), absolute humidity (AH) (β = 0.2476, p = 0.002), P × AH (β = −0.2237, p < 0.001), and NM (β = 0.1383, p = 0.003) are more significant determinants of R, as compared to GDP per capita (β = 0.1115, p = 0.015) and CM (Asthma) (β = 0.1273, p = 0.005). A matching technique was adopted to demonstrate a possible causal relationship between P and R across 18 provincial capital cities. A 10 µg/m3 increase in P gives a 1.5% increase in R (p < 0.001). Interaction analysis also reveals that P × AH and R are negatively correlated (β = −0.2237, p < 0.001). Given that P exacerbates R, we recommend the installation of air purifiers and improved air ventilation to reduce the effect of P on R. Given the increasing observation that COVID-19 is airborne, measures that reduce P, plus mandatory masking that reduces the risks of COVID-19 associated with viral-particulate transmission, are strongly recommended. Our study is distinguished by the focus on the rate of change instead of the individual cases of COVID-19 when modelling the statistical relationship between R and P in China; causal instead of correlation analysis via the matching analysis, while taking into account the key confounders, and the individual plus the interaction effects of P and AH on R.
format	article
author	Yang Han Jacqueline C. K. Lam Victor O. K. Li Jon Crowcroft Jinqi Fu Jocelyn Downey Illana Gozes Qi Zhang Shanshan Wang Zafar Gilani
author_facet	Yang Han Jacqueline C. K. Lam Victor O. K. Li Jon Crowcroft Jinqi Fu Jocelyn Downey Illana Gozes Qi Zhang Shanshan Wang Zafar Gilani
author_sort	Yang Han
title	Outdoor PM2.5 concentration and rate of change in COVID-19 infection in provincial capital cities in China
title_short	Outdoor PM2.5 concentration and rate of change in COVID-19 infection in provincial capital cities in China
title_full	Outdoor PM2.5 concentration and rate of change in COVID-19 infection in provincial capital cities in China
title_fullStr	Outdoor PM2.5 concentration and rate of change in COVID-19 infection in provincial capital cities in China
title_full_unstemmed	Outdoor PM2.5 concentration and rate of change in COVID-19 infection in provincial capital cities in China
title_sort	outdoor pm2.5 concentration and rate of change in covid-19 infection in provincial capital cities in china
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/816e12d7d07f4da695dae48ab68dc4a0
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Outdoor PM2.5 concentration and rate of change in COVID-19 infection in provincial capital cities in China

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