|本期目录/Table of Contents|

[1]时欣培,雷 静,苗志峰,等.银川市风疹发病趋势的预测方法初探[J].宁夏医科大学学报,2018,(03):301-305.[doi:10.16050/j.cnki.issn1674-6309.2018.03.011]
 SHI Xinpei,LEI Jing,MIAO Zhifeng,et al.Preliminary Study on Forecasting Trend of Rubella Incidence in Yinchuan[J].Ningxia Medical University,2018,(03):301-305.[doi:10.16050/j.cnki.issn1674-6309.2018.03.011]
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银川市风疹发病趋势的预测方法初探(PDF)
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《宁夏医科大学学报》[ISSN:1005-8486/CN:64-1029/R]

卷:
期数:
2018年03期
页码:
301-305
栏目:
论 著
出版日期:
2018-03-30

文章信息/Info

Title:
Preliminary Study on Forecasting Trend of Rubella Incidence in Yinchuan
作者:
时欣培1 雷 静2 苗志峰3 张伟宏3
(1. 宁夏医科大学,银川 750004; 2. 银川市卫生计生委,银川 750011; 3. 银川市疾病预防控制中心,银川 750011)
Author(s):
SHI Xinpei1 LEI Jing2 MIAO Zhifeng3 ZHANG Weihong3
(1. Ningxia Medical University,Yinchuan 750004; 2. Yinchuan Health and Family Planning Commission,Yinchuan 750011; 3.Yinchuan Municipal Center for Disease Control and Prevention,Yinchuan 750011)
关键词:
时间序列分析统计预测风疹发病率银川宁夏
Keywords:
time series analysis statistical prediction rubella incidence rateYinchuanNingxia
分类号:
R183.3
DOI:
10.16050/j.cnki.issn1674-6309.2018.03.011
文献标志码:
A
摘要:
目的 运用动态数列、回归模型法(非线性回归)和指数平滑法对银川市风疹发病率进行预测,为银川市传染病发病情况的科学预测以及防控工作提供科学依据。方法 以时间序列为基础利用SPSS和Excel建立数据模型,分别运用三种方法对银川市2009-2015年风疹发病率进行预测,并比较3种方法的发病率预测值与实际发病率,同时计算预测误差(SDE),对预测效果进行评价分析。结果 动态数列法、非线性回归法及指数平滑法对银川市2009-2015年风疹发病率的预测值与实际发病率比较差异均无统计学意义(t=-0.314/-0.507/-1.183,P=0.753/0.612/0.217)。3种方法对银川市2016年风疹年发病率的预测值依次为:2.29/10万、1.18/10万、2.25/10万。其SDE依次为:15.79、2.28、9.59。结论 非线性回归法、指数平滑法、动态数列法可用于银川市风疹发病率的预测,且预测精度依次降低。
Abstract:
Objective To make prediction of the infectious diseases incidence in Yinchuan more scientifically and to provide credible basis for contagion control by using of dynamic series, regression model (nonlinear regression) and exponential smoothing method. Methods According to the time serious, using SPSS and Excel to establish the data model to forecast the incidence rate of rubella in Yinchuan in 2016. Then,comparing each year's predicted value and actual measured value by different forecasting methods and comparing the SDE values,in order to evaluate prediction performance. Results For each frecasting methods,there were no significance between predicted value and actual measured value(t=-0.314/-0.507/-1.183,P=0.753/0.612/0.217).The predicted rubella incidence of the three approaches in sequence were 2.29 per 10 million,1.18 per 10 million,2.25 per 10 million respectively. The SDE values in proper order were 15.79,2.28,9.59. Conclusion For this time serious,the models above-mentioned are available to be used in forecasting the rubella incidence in Yinchuan. The prediction accuracy of the models from high to low is nonlinear regression, exponential smoothing method and dynamic series method.

参考文献/References:


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备注/Memo

备注/Memo:
收稿日期:2017-12-21
作者简介:时欣培,女,在读硕士研究生,研究方向:流行病学。E-mail: 459613729@qq.com
通信作者:雷静,女,主任医师,硕士研究生导师,从事流行病学研究教育工作。E-mail: jk_lei@126.com
更新日期/Last Update: 2018-03-30