Region-specific air pollutants and meteorological parameters influence COVID-19: A study from mainland China

Abstract

Coronavirus disease 2019 (COVID-19) was first detected in December 2019 in Wuhan, China, with 11,669,259 positive cases and 539,906 deaths globally as of July 8, 2020. The objective of the present study was to determine whether meteorological parameters and air quality affect the transmission of COVID-19, analogous to SARS. We captured data from 29 provinces, including numbers of COVID-19 cases, meteorological parameters, air quality and population flow data, between Jan 21, 2020 and Apr 3, 2020. To evaluate the transmissibility of COVID-19, the basic reproductive ratio (R₀) was calculated with the maximum likelihood "removal" method, which is based on chain-binomial model, and the association between COVID-19 and air pollutants or meteorological parameters was estimated by correlation analyses. The mean estimated value of R₀ was 1.79 ± 0.31 in 29 provinces, ranging from 1.08 to 2.45. The correlation between R₀ and the mean relative humidity was positive, with coefficient of 0.370. In provinces with high flow, indicators such as carbon monoxide (CO) and 24-h average concentration of carbon monoxide (CO_24 h) were positively correlated with R₀, while nitrogen dioxide (NO₂), 24-h average concentration of nitrogen dioxide (NO₂_24 h) and daily maximum temperature were inversely correlated to R₀, with coefficients of 0.644, 0.661, -0.636, -0.657, -0.645, respectively. In provinces with medium flow, only the weather factors were correlated with R₀, including mean/maximum/minimum air pressure and mean wind speed, with coefficients of -0.697, -0.697, -0.697 and -0.841, respectively. There was no correlation with R₀ and meteorological parameters or air pollutants in provinces with low flow. Our findings suggest that higher ambient CO concentration is a risk factor for increased transmissibility of the novel coronavirus, while higher temperature and air pressure, and efficient ventilation reduce its transmissibility. The effect of meteorological parameters and air pollutants varies in different regions, and requires that these issues be considered in future modeling disease transmissibility.

Keywords: Air pollutant; Basic reproductive ratio; COVID-19; Meteorological parameter.

Graphical abstract

Fig. 1

The values of R₀ in 29 provinces, China.

Fig. 2

The trend between R₀ and meteorological factors. A. R₀ and maximum temperature; B. R₀ and mean wind velocity; C. R₀ and mean air pressure; D. R₀ and minimum air pressure; E. R₀ and maximum air pressure. Blue, high flow; red, medium flow; green, low flow. Solid line means significant association between observation variable and COVID-19, dotted line means no significant association between observation variable and COVID-19. . (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3

The trend between R₀ and air quality factors. A. R₀ and CO; B. R₀ and CO_24 h; C. R₀ and NO₂; D. R₀ and NO₂_24 h; Blue, high flow; red, medium flow; green, low flow. Solid line means significant association between observation variable and COVID-19, dotted line means no significant association between observation variable and COVID-19. . (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)