In recent 2 years, the incidence of influenza showed a slight upward trend in Guangxi; therefore, some joint actions should be done to help preventing and controlling this disease. The factors analysis of affecting influenza and early prediction of influenza incidence may help policy-making so as to take effective measures to prevent and control influenza. In this study, we used the cross correlation function (CCF) to analyze the effect of climate indicators on influenza incidence, ARIMA and ARIMAX (autoregressive integrated moving average model with exogenous input variables) model methods to do predictive analysis of influenza incidence. The results of CCF analysis showed that climate indicators (PM2.5, PM10, SO2, CO, NO2, O3, average temperature, maximum temperature, minimum temperature, average relative humidity, and sunshine duration) had significant effects on the incidence of influenza. People need to take good precautions in the days of severe air pollution and keep warm in cold weather to prevent influenza. We found that the ARIMAX (1,0,1)(0,0,1)12 with NO2 model has good predictive performance, which can be used to predict the influenza incidence in Guangxi, and the predicted incidence may be useful in developing early warning systems and providing important evidence for influenza control policy-making and public health intervention.
Environmental Science and Pollution Research - The concentrations of major and trace elements in the sediments from the Four River inlets of Dongting Lake were analysed. The results show that the... 相似文献
Environmental Science and Pollution Research - There is an increasing number of studies focusing on extreme weather all over the world, but global trends and research topics related to extreme... 相似文献
Atrazine, a widely used herbicide, is increasing the agricultural production effectively, while also causing great environmental concern. Efficient atrazine-degrading bacterium is necessary to removal atrazine rapidly to keep a safe environment. In the present study, a new atrazine-degrading strain ZXY-1, identified as Pseudomonas, was isolated. This new isolated strain has a strong ability to biodegrade atrazine with a high efficiency of 9.09 mg/L/hr.Temperature, p H, inoculum size and initial atrazine concentration were examined to further optimize the degradation of atrazine, and the synthetic effect of these factors were investigated by the response surface methodology. With a high quadratic polynomial mathematical model(R~2= 0.9821) being obtained, the highest biodegradation efficiency of 19.03 mg/L/hr was reached compared to previous reports under the optimal conditions(30.71°C, pH 7.14, 4.23%(V/V) inoculum size and 157.1 mg/L initial atrazine concentration).Overall, this study provided an efficient bacterium and approach that could be potentially useful for the bioremediation of wastewater containing atrazine. 相似文献