Using ARIMA model to surveillance and forecast the incidence rate of notifiable infectious diseases in Chongqing
- VernacularTitle:重庆市法定报告传染病预测与监测的ARIMA模型
- Author:
Mengliang YE
- Publication Type:Journal Article
- Keywords:
Time series;
Model of autoregressive integrated moving average;
Prediction
- From:
Journal of Chongqing Medical University
2007;0(08):-
- CountryChina
- Language:Chinese
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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.
