Using ARIMA model to surveillance and forecast the incidence rate of notifiable infectious diseases in Chongqing

YE Meng-liang; et al

您当前的位置：

首页 >

文章列表页 >

Using ARIMA model to surveillance and forecast the incidence rate of notifiable infectious diseases in Chongqing

更新时间：2024-01-17

- Using ARIMA model to surveillance and forecast the incidence rate of notifiable infectious diseases in Chongqing
- Journal of Chongqing Medical University Vol. 34, Issue 8, Pages: 1070-1072(2009)
- 作者机构：
  
  1. 重庆医科大学公共卫生学院卫生统计与信息管理教研室
  2. 重庆市荣昌县人民医院
- 作者简介：
- 基金信息：
- DOI：
  CLC： R181.8
- Published：2009，
扫描看全文
[1]叶孟良,张多西,王润华.重庆市法定报告传染病预测与监测的ARIMA模型[J].重庆医科大学学报,2009,34(08):1070-1072.

YE Meng-liang, et al. Using ARIMA model to surveillance and forecast the incidence rate of notifiable infectious diseases in Chongqing. [J]. Journal of Chongqing Medical University 34(8):1070-1072(2009)
[1]叶孟良,张多西,王润华.重庆市法定报告传染病预测与监测的ARIMA模型[J].重庆医科大学学报,2009,34(08):1070-1072. DOI：

YE Meng-liang, et al. Using ARIMA model to surveillance and forecast the incidence rate of notifiable infectious diseases in Chongqing. [J]. Journal of Chongqing Medical University 34(8):1070-1072(2009) DOI：

摘要

目的:通过对2003年1月～2008年12月重庆市法定报告传染病逐月发病率数据的分析

研究其变化规律

建立预测与监测的ARIMA时间序列模型。方法:用Box-Ljung统计量评价ARIMA模型的拟合度

用平均预测相对误差作为预测效果的评价指标。结果:重庆市法定报告传染病发病以年为周期

1年中4～6月为高发月

尤其是5月和6月最为严重。ARIMA（0

0）（0

1）12模型是重庆市法定报告传染病拟合的最佳模型

其拟合残差的方差为12.23

外推预测的平均相对误差为8.3%。结论:对传染病发病率历史数据进行时间序列分析是用于传染病监测的一个重要的内容。本研究所建立的ARIMA模型适用于重庆市传染病发病率预测与监测。

Abstract

Objective:To develop the model for forecasting and surveilling the spread of notifiable infectious diseases in Chongqing.Methods:Statistics of Box-Ljung was used to evaluate the degree of fitness of ARIMA model

and the average relative errors of predict were used as indexes to evaluate the predict effect.Results:The changes of incidence rate of the notifiable infectious diseases in Chongqing presented a yearly periodicity

and showed that the incidence rate from March to August exceeded the monthly average of it.The residuals sum of square of the ARIMA model was 12.23 for incidence rate of the notifiable infectious disease from 2003 to 2007

and the mean relative error of the model was 8.3%.Conclusion:Time series methods applied to historical reporting data of infectious disease are an important tool for infectious disease surveillance.The ARIMA model is suitable to forecast the incidence rate of notifiable infectious diseases in Chongqing.Our approach potentially has a high practical value in forecasting and surveilling the notifiable infectious diseases.

关键词

时间序列ARIMA模型预测

Keywords

time seriesModel of autoregressive integrated moving averageprediction

references

Views

262

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Applications of multiple seasonal ARlMA model on predictive workload of inpatient department

Prediction of influenza in Chongqing，China，based on the Autoregressive Integrated Moving Average model

Predictive value of NLR and PLR for outcome after immunotherapy in advanced urothelial carcinoma

Prediction of endoscopic disease activity by analyzing blood biochemical results in children with Crohn's disease

Value of carbohydrate antigen 125, human chorionic gonadotropin and progesterone in predicting pregnancy outcome in patients with threatened abortion at early stage

Related Author

LIU Jin-lian

et al

Zou Xiaojiang

Zhao Han

Wang Qiyin

Ye Mengliang

Chen Yingye

Sun Wei

Related Institution

重庆医科大学公共卫生学院卫生统计教研室

Department of Statistics,College of Public Health,Chongqing Medical University

Chongqing Center for Disease Control and Prevention

School of Public Health，Chongqing Medical University

Department of Urology,The Second Affiliated Hospital of Chongqing Medical University

⁰