Application and comparison of three models for the prediction of influenza-like illness in Jiangxi Province
10.16462/j.cnki.zhjbkz.2019.01.021
- Author:
Wei-jie FU
1
;
Yun XIE
;
Zhi-li ZENG
;
Xiao-qing LIU
Author Information
1. Communicable Disease Control and Prevention, Center for Disease Control and Prevention of Jiangxi Provence, Nanchang 330029, China
- Publication Type:Journal Article
- Keywords:
Influenza-like illness;
Autoregressive Integrated Moving Average;
Forecast;
Error
- From:
Chinese Journal of Disease Control & Prevention
2019;23(1):101-105
- CountryChina
- Language:Chinese
-
Abstract:
Objective To establish the optimal epidemical trend prediction model of influenza in Jiangxi Province and provide scientific guidance for influenza prevention and control. Methods Monthly influenza sentinel surveillance data of Jiangxi Province were derived from the “Influenza Surveillance Information System In China” from 2013 to 2017, and the different forecasting methods were used to build model, such as autoregressive(AR),exponential smoothing(ES) and autoregressive integrated moving average(ARIMA), also compared predictions with actual values in 2017. Results R square of the three models were 0.731, 0.751 and 0.815 respectively; the root mean square error(MRSE) were 0.253, 0.243 and 0.212, respectively; mean absolute error(MAE)were 0.189, 0.178 and 0.151, respectively; mean absolute percentage error(MAPE) were 10.092, 9.523 and 8.124 respectively; the average relative error (MRE) were 11.45%, 10.92% and 8.96%, respectively. Conclusions ARIMA was a good model for predicting the percentage of influenza-like illness in outpatient visits in Jiangxi Province.
