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 Belt and Road Initiative (BRI) is closely linked to the ecological sustainability of the infrastructure ventures that intrinsically include the... 相似文献
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In 2013,China issued "Air Pollution Prevention and Control Action Plan(Action Plan)" to improve air quality.To assess the benefits of this program in Beijing-Tianjin-Hebei(BTH)region,where the density of population and emissions vary greatly,we simulated the air quality benefit based on Ben MAP to satisfy the Action Plan.In this study,we estimate PM_(2.5) concentration using Voronoi spatial interpolation method on a grid with a spatial resolution of 1 × 1 km~2.Combined with the exposure-response function between PM_(2.5) concentration and health endpoints,health effects of PM_(2.5) exposure are analyzed.The economic loss is assessed by using the willingness to pay(WTP) method and human capital(HC) method.When the PM_(2.5) concentration falls by 25% in BTH and reached 60 μg/m~3 in Beijing,the avoiding deaths will be in the range of 3175 to 14051 based on different functions each year.Of the estimated mortality attributable to all causes,3117 annual deaths were due to lung cancer,1924 – 6318 annual deaths were due to cardiovascular,and343 – 1697 annual deaths were due to respiratory.Based on WTP,the estimated monetary values for the avoided cases of all cause mortality,cardiovascular mortality,respiratory mortality and lung cancer ranged from 1110 to 29632,673 to 13325,120 to 3579,1091 to 6574 million yuan,respectively.Based on HC,the corresponding values for the avoided cases of these four mortalities were 267 to 1178,161 to 529,29 to 143 and 261 million yuan,respectively. 相似文献