ABSTRACT
Objective To explore the temporal and spatial distribution characteristics of air pollutants PM2.5, PM10, SO2, CO, and NO2, and their effects on acute cerebrovascular diseases in Jining City. Methods The data of patients with acute cerebrovascular disease treated in a 3A hospital in Jining from October 1, 2017, to November 31, 2019, were retrospectively collected. Combined with the air pollution data of 29 air quality monitoring stations in Jining City, the Kriging interpolation model was used to analyze the overall situation of air pollution in Jining. On this basis, the relationship between air pollution and acute cerebrovascular diseases in Jining City was analyzed. Results In Jining City, the incidence of acute cerebrovascular disease in male was higher than that in female, and the incidence in rural areas was significantly higher than that in urban areas. The spatial distribution showed a trend of gradual accumulation from southeast to northwest. The daily average concentrations of PM2.5 and PM10 were higher in winter and spring than in summer and autumn. The results of Kriging interpolation analysis showed that the concentrations of these air pollutants formed aggregation points in varying degrees. The spatial distribution of acute cerebrovascular disease patients in Jining City was highly consistent with the spatial distribution of air pollutant concentrations. Spearman correlation analysis showed that CO, SO2, and NO2 were positively correlated with the incidence of acute cerebrovascular disease, while the correlation between PM2.5 and PM10 and the incidence of acute cerebrovascular disease was not significant. Conclusion Some air pollutants such as CO, SO2, and NO2 have a positive correlation with the incidence of acute cerebrovascular disease, and the prevalence has a certain population and regional distribution. In the future work of cerebrovascular disease prevention, personal protection should be done according to local conditions and living environment of specific people.
ABSTRACT
Objective To understand the distribution of the severe fever with thrombocytopenia syndrome (SFTS) in Zhejiang province,and predict the incidence and the probability of SFTS outbreak.Methods Based on the cases of SFTS from 2011-2015,software ArcGIS 10.0 was used to analyze the spatial distribution,Moran's I and Getis-Ord Gi were used to analyze the spatial autocorrelation.The incidence trend was explored by trend surface analysis,and the prediction was made by Kriging interpolation.Results The incidence of SFTS increased and the distribution expanded in Zhejiang from 2011 to 2015,the seasonal and the demographic characteristics of SFTS were similar to the previous research;there were regional clustering of the cases (P＜0.001);a downward trend was observed from northeast to southwest in terms of incidence of SFTS;the second-order disjunctive Kriging interpolation based on circular model and the indicator Kriging interpolation based on exponential model had higher prediction accuracy,the probabilities of outbreak in Anji,Daishan and Tiantai were high,the prediction deviation of inland was less than that of edge area.Conclusion The prediction of SFTS by Kriging interpolation had high accuracy,the incidence of SFTS was higher and the distribution of SFTS was larger than the results of surveillance,the risk areas for epidemic were Anji,Daishan,Ninghai,Tiantai,Sanmen and Linhai.
ABSTRACT
Objective To understand the distribution of the severe fever with thrombocytopenia syndrome (SFTS) in Zhejiang province,and predict the incidence and the probability of SFTS outbreak.Methods Based on the cases of SFTS from 2011-2015,software ArcGIS 10.0 was used to analyze the spatial distribution,Moran's I and Getis-Ord Gi were used to analyze the spatial autocorrelation.The incidence trend was explored by trend surface analysis,and the prediction was made by Kriging interpolation.Results The incidence of SFTS increased and the distribution expanded in Zhejiang from 2011 to 2015,the seasonal and the demographic characteristics of SFTS were similar to the previous research;there were regional clustering of the cases (P＜0.001);a downward trend was observed from northeast to southwest in terms of incidence of SFTS;the second-order disjunctive Kriging interpolation based on circular model and the indicator Kriging interpolation based on exponential model had higher prediction accuracy,the probabilities of outbreak in Anji,Daishan and Tiantai were high,the prediction deviation of inland was less than that of edge area.Conclusion The prediction of SFTS by Kriging interpolation had high accuracy,the incidence of SFTS was higher and the distribution of SFTS was larger than the results of surveillance,the risk areas for epidemic were Anji,Daishan,Ninghai,Tiantai,Sanmen and Linhai.