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 human morbidity 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.
［摘要］目的 掌握安徽省池州市贵池区血吸虫病流行规律, 为制定防治措施提供参考依据。方法 收集1991–2011 年贵池区血吸虫病疫情资料, 采用描述性统计方法, 统计病情、螺情等血吸虫病疫情指标。应用自回归求和移动平均模 型 (Autoregressive integrated moving average, ARIMA) 分析该地区血吸虫病发病率的变化趋势。结果 不同血吸虫病流行 类型地区的实际有螺面积差异有统计学意义 (F = 256.79, P < 0.05), 人群患病率随钉螺实际有螺面积的增加而升高 (P < 0.05), 并且有4个波动高峰 (1992、1995、2005、2008年) 。时间序列分析显示ARIMA (1, 1, 1) 是拟合最优模型, 短期预测 2012–2015年贵池区血吸虫病发病率分别为0.017%、0.007%、0.012%和0.010%。结论 贵池区血吸虫病疫情得到了有 效控制, 但湖滩地区仍应加强监测, 以防止疫情回升。.
Keywords: Chizhou City; Endemic situation; Oncomelania hupensis; Schistosomiasis; Surveillance.