Objective To explore the technique of maximum entropy model for extracting Oncomelania hupensis snail habi?tats in Poyang Lake zone. Methods The information of snail habitats and related environment factors collected in Poyang Lake zone were integrated to set up the maximum entropy based species model and generate snail habitats distribution map. Two Land?sat 7 ETM+remote sensing images of both wet and drought seasons in Poyang Lake zone were obtained,where the two indices of modified normalized difference water index(MNDWI)and normalized difference vegetation index(NDVI)were applied to ex?tract snail habitats. The ROC curve,sensitivities and specificities were applied to assess their results. Furthermore,the impor?tance of the variables for snail habitats was analyzed by using Jackknife approach. Results The evaluation results showed that the area under receiver operating characteristic curve(AUC)of testing data by the remote sensing?based method was only 0.56, and the sensitivity and specificity were 0.23 and 0.89 respectively. Nevertheless,those indices above?mentioned of maximum en?tropy model were 0.876,0.89 and 0.74 respectively. The main concentration of snail habitats in Poyang Lake zone covered the northeast part of Yongxiu County,northwest of Yugan County,southwest of Poyang County and middle of Xinjian County,and the elevation was the most important environment variable affecting the distribution of snails,and the next was land surface tem?perature(LST). Conclusions The maximum entropy model is more reliable and accurate than the remote sensing?based meth?od for the sake of extracting snail habitats,which has certain guiding significance for the relevant departments to carry out mea?sures to prevent and control high?risk snail habitats.

Objective To understand the epidemical patterns of schistosomiasis in Guichi District of Chizhou City，Anhui Province，in order to provide the reference for schistosomiasis control. Methods The annual data of schistosomiasis endemic situation in Guichi District from 1991 to 2011 were collected. The descriptive analysis was first conducted to describe the changes of schistosomiasis in local residents and the status of Oncomelania hupensis. An autoregressive integrated moving average （ARIMA）model was applied to fit and predict the tendency of schistosomiasis incidence in this region. Results The humanmorbidity increased with the increasing of the areas with snail habitats（P < 0.05），and four peaks（in 1992，1995，2005，2008）were detected. The difference of the area with snails among different types of snail habitats was statistically significant（F = 256.79，P < 0.05）. ARIMA（1，1，1）was determined to be the optimal model for analyzing the morbidity of schistosomiasis，and the short⁃term forecast of the morbidity in Guichi District from 2012 to 2015 showed that the predicted values were 0.017%，0.007%，0.012%，and 0.010%，respectively. Conclusions The endemic situation of schistosomiasis in Guichi District is controlled relatively well in the past two decades. However，the surveillance in the lake and marshland regions should be strengthened continuously to prevent the rebounding of the schistosomiasis endemic situation.