摘要
目的分析2012—2020年石家庄市流感发病相关数据并建立预测模型,预测石家庄市2021年流感发病趋势。方法利用Excel和数理统计学相结合的方法,根据时间序列数据的特点对石家庄市流感发病数据使用哑变量多重回归、自回归模型和季节指数法进行数据分析和模型拟合,并进行流感发病预测。结果哑变量多重回归的平均相对误差为0.90%,自回归模型的平均相对误差为3.62%,季节指数法的平均相对误差为1.34%。结果表明哑变量多重回归相对误差更小、精确度更高、更接近真实数据,其次为季节指数法、自回归模型。结论要善于运用Excel等常用工具开展疾病监测数据分析,了解疾病发生发展规律,为疾病防控措施的制定提供数据支持。
Objective To predict the trend of influenza incidence of Shijiazhuang in 2021 by analyzing related data of influenza incidence in Shijiazhuang from 2012 to 2020 and establishing the prediction model.Methods The method combining Excel and mathematical statistics was applied,multiple regression with dummy variable,autoregressive model and seasonal index method were used based on the characteristics of time series data to analyze and fit the data of influenza incidence in Shijiazhuang,and the incidence of influenza was predicted.Results The average relative error of multiple regression with dummy variable was 0.90%,and such index of autoregressive model and seasonal index method was 3.62%and 1.34%,respectively.The results showed that the multiple regression model with dummy variable was found to have less relative error,higher accuracy and be closer to real data,followed by seasonal index method and autoregressive model.Conclusion It is suggested to skillfully apply Excel and other common tools to implemented disease surveillance data analysis,understand the law for disease attack and development,and provide data support for formulating disease prevention and control measures.
作者
史晓董
刘立
史艳
万丽
赵冬
张世勇
SHI Xiao-dong;LIU Li;SHI Yan;WAN Li;ZHAO Dong;ZHANG Shi-yong(Graduate School,Hebei Medical University,Shijiazhuang 050017,China;不详)
出处
《医学动物防制》
2022年第6期539-543,共5页
Journal of Medical Pest Control
基金
2021年中央基本公共卫生服务项目—石家庄市重点传染病防治项目(石卫办疾控函[2021]8号)。
关键词
EXCEL
流感预测方法
数据分析
疾病防控
时间序列
Excel
Prediction method for influenza
Data analysis
Disease prevention and control
Time series
