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灰色模型预测全国慢性宫颈炎流行趋势
引用本文:刘瑜新,宋晓勇,张世清,刘强,张红霞,杨磊,张永州.灰色模型预测全国慢性宫颈炎流行趋势[J].中原医刊,2011(22):1-3.
作者姓名:刘瑜新  宋晓勇  张世清  刘强  张红霞  杨磊  张永州
作者单位:[1]河南大学淮河医院,开封475000 [2]河南大学药学院,开封475000
摘    要:目的应用灰色模型GM(1,1)对全国慢性宫颈炎在妇科疾病中的年发病率进行预测。方法采用1999年至2009年慢性宫颈炎发病率数据建立GM(1,1)模型,并用平均相对误差、后验差比值(c值)和小误差概率(P值)来检验灰色数列模型的可靠性,预测2010年至2013年的发病率。结果通过以上数据得出GM(1,1)模型:Y(t)=903.56。0.0122(t-1)-893.22。经拟合检验,模型拟合精度好(C=0.41,P=0.90)。利用本模型对2010年至2013年全国慢性宫颈炎的发病率进行外推,估计2010年至2013年全国慢性宫颈炎的发病率分别为12.53%、12.68%、12.84%、13.00%。结论通过灰色模型预测慢性宫颈炎的发病率有缓慢增高的趋势,提示卫生管理部门应加强慢性宫颈炎的防治工作。

关 键 词:灰色模型  慢性宫颈炎  预测

Grey model in forecasting trends of chronic cervicitis in mainland China
LIU Yu-xin,SONG Xiao-yong,ZHANG Shi-qing,LIU Qiang,ZHANG Hong-xia,YANG Lei,ZHANG Yong-zhou.Grey model in forecasting trends of chronic cervicitis in mainland China[J].Central Plains Medical Journal,2011(22):1-3.
Authors:LIU Yu-xin  SONG Xiao-yong  ZHANG Shi-qing  LIU Qiang  ZHANG Hong-xia  YANG Lei  ZHANG Yong-zhou
Institution:. (Huaihe Hos- pital of Henan University, Kaifeng 475000, China)
Abstract:Objective To forecast the trends of chronic cervicitis in mainland China with grey model GM ( 1,1 ), and to assess the predictability of these models. Methods GM ( 1,1 ) model was developed based on the yearly incidence from 1999 to 2009. Relative error, posterior deviation ratio ( C val- ue) and small error probability ( P value) was used to validate the predictability of the model. And the model was used to predict the yearly incidence from 2010 to 2013. Results The preferable model to forecast the yearly trends of chronic cervieitis was Y(t) = 903.56e~~1=~t-1~ - 893.22. Their corre- spond relative error was 1.70% , C = 0.41 and P = 0.90. The estimated yearly incidence for chron- ic eervieitis from 2010 to 2013 were 12.53% , 12.68% , 12.84% and 13.00% , respectively. Conclusions Grey model forecasted that the incidence of chronic cervicitis were increased. It sug- gested that health authorities should strengthen the prevention and treatment of chronic cervicitis.
Keywords:Grey model  Chronic cervicitis  Forecast
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