HE Miao,SHI Changhao,SHE Xuanjie,et al.Spatial-temporal characteristics and pollutant assessment in the early stage of COVID-19 outbreak in China[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2022,61(04):11-21.
HE Miao,SHI Changhao,SHE Xuanjie,et al.Spatial-temporal characteristics and pollutant assessment in the early stage of COVID-19 outbreak in China[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2022,61(04):11-21. DOI: 10.13471/j.cnki.acta.snus.2021E002.
Spatial-temporal characteristics and pollutant assessment in the early stage of COVID-19 outbreak in China
To explore the early stage spatial-temporal characteristics and to assess the factors of atmospheric pollution that may affect the development of coronavirus disease 2019 (COVID-19) outbreak in the Chinese Mainland in 2020, we collected the daily new cases of COVID-19 in the Municipalities and Provinces from the websites of National and Provincial Health Commission of China. The spatio-temporal characteristics of COVID-19 epidemic were studied using autocorrelation analysis and trend analysis. The Spearman's correlation coefficient for ranked data and generalized additive model were used for risk assessment of air pollutants affecting the COVID-19 epidemic of Hubei Province. Daily new cases of COVID-19 in the Chinese Mainland totaled 39 877 from January 20th to February 9th of 2020. The global Moran index values of these three weeks were 0.249, 0.307 and 0.297 (
P
<
0.01), respectively. There was a significant clustering phenomenon. The high incidence regions included Hunan Province, Guangdong Province, Jiangxi Province, Zhejiang Province, Anhui Province and Jiangsu Province. The epidemic hot spots were basically distributed in the area from 108° 47'-123° 10' E to 25° 31'-35° 20' N. Daily new cases of COVID-19 in Hubei Province was positively correlated with daily average concentrations of PM
10
, NO
2
and O
3
pollutants (
ρ
=0.515, 0.579 and 0.536,
P
<
0.05). The lag effects of air pollutions were existed. The relative risk (RR) values of PM
2.5
and PM
10
reached to maximum with lag0, the RR value of NO
2
reached to maximum with lag4, and the RR value of O
3
reached to maximum with lag 0~1. We estimated that a 10 μg/m
3
increase in day-before NO
2
daily average concentration was associated with a 32.745% (95% Confidence Interval (CI):11.586%-57.916%) excess risk (ER) of daily new cases of COVID-19. And NO
2
had a significant impact on daily new cases of COVID-19. When NO
2
was introduced to PM
2.5
and PM
10
separately, for every 10 μg/m
3
rise in NO
2
daily average concentration, the ER of daily new cases of COVID-19 was 23.929% (95% CI: 4.705%-46.682%) and 24.672% (95% CI: 5.379%-47.496%), respectively. The study showed that the southeast was the main spread direction in the early stage of COVID-19 outbreak in the Chinese Mainland in 2020. Reducing the atmospheric concentration of nitrogen dioxide in epidemic hot spots has a positive effect on epidemic prevention and control.
coronavirus disease 2019(COVID-19)early stage of outbreak in 2020spatial-temporal characteristicsrisk assessment
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