Comparison of Two Hybrid Models for Forecasting the Incidence of Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China.
BACKGROUND
Cases of hemorrhagic fever with renal syndrome (HFRS) are widely distributed in eastern Asia, especially in China, Russia, and Korea. It is proved to be a difficult task to eliminate HFRS completely because of the diverse animal reservoirs and effects of global warming. Reliable forecasting is useful for the prevention and control of HFRS.


METHODS
Two hybrid models, one composed of nonlinear autoregressive neural network (NARNN) and autoregressive integrated moving average (ARIMA) the other composed of generalized regression neural network (GRNN) and ARIMA were constructed to predict the incidence of HFRS in the future one year. Performances of the two hybrid models were compared with ARIMA model.


RESULTS
The ARIMA, ARIMA-NARNN ARIMA-GRNN model fitted and predicted the seasonal fluctuation well. Among the three models, the mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of ARIMA-NARNN hybrid model was the lowest both in modeling stage and forecasting stage. As for the ARIMA-GRNN hybrid model, the MSE, MAE and MAPE of modeling performance and the MSE and MAE of forecasting performance were less than the ARIMA model, but the MAPE of forecasting performance did not improve.


CONCLUSIONS
Developing and applying the ARIMA-NARNN hybrid model is an effective method to make us better understand the epidemic characteristics of HFRS and could be helpful to the prevention and control of HFRS.
Department of Epidemiology, School of Public Health, China Medical University, Shenyang, PR China.
Wei
W
Wu
Liaoning Provincial Center for Disease Control and Prevention, Shenyang, PR China.
Junqiao
J
Guo
Liaoning Provincial Center for Disease Control and Prevention, Shenyang, PR China.
Shuyi
S
An
Department of Epidemiology, School of Public Health, China Medical University, Shenyang, PR China.
Peng
P
Guan
Department of Epidemiology, School of Public Health, China Medical University, Shenyang, PR China.
Yangwu
Y
Ren
Department of Epidemiology, School of Public Health, China Medical University, Shenyang, PR China.
Linzi
L
Xia
Department of Epidemiology, School of Public Health, China Medical University, Shenyang, PR China.
Baosen
B
Zhou
D002681:China / Q000453:epidemiology; D005544:Forecasting; D006480:Hemorrhagic Fever with Renal Syndrome / Q000453:epidemiology*; D006801:Humans; D015994:Incidence; D015233:Models, Statistical; D056910:Republic of Korea / Q000453:epidemiology; D012426:Russia / Q000453:epidemiology; D012984:Software