Application of an Autoregressive Integrated Moving Average Model for Predicting the Incidence of Hemorrhagic Fever with Renal Syndrome

The Box-Jenkins approach was used to fit an autoregressive integrated moving average (ARIMA) model to the incidence of hemorrhagic fever with renal Syndrome (HFRS) in China during 1986-2009. The ARIMA (0, 1, 1) × (2, 1, 0)(12) models fitted exactly with the number of cases during January 1986-Decemb...

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Bibliographic Details
Published in:The American journal of tropical medicine and hygiene 2012-08, Vol.87 (2), p.364-370
Main Authors: QI LI, GUO, Na-Na, HAN, Zhan-Ying, ZHANG, Yan-Bo, QI, Shun-Xiang, XU, Yong-Gang, WEI, Ya-Mei, XU HAN, LIU, Ying-Ying
Format: Article
Language:English
Subjects:
Biological and medical sciences
China - epidemiology
Forecasting
Hemorrhagic Fever with Renal Syndrome - epidemiology
Human viral diseases
Humans
Incidence
Infectious diseases
Lassa fever and arenovirus diseases
Medical sciences
Models, Statistical
Seasons
Tropical viral diseases
Viral diseases
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Summary:The Box-Jenkins approach was used to fit an autoregressive integrated moving average (ARIMA) model to the incidence of hemorrhagic fever with renal Syndrome (HFRS) in China during 1986-2009. The ARIMA (0, 1, 1) × (2, 1, 0)(12) models fitted exactly with the number of cases during January 1986-December 2009. The fitted model was then used to predict HFRS incidence during 2010, and the number of cases during January-December 2010 fell within the model's confidence interval for the predicted number of cases in 2010. This finding suggests that the ARIMA model fits the fluctuations in HFRS frequency and it can be used for future forecasting when applied to HFRS prevention and control.
ISSN:0002-9637
1476-1645
DOI:10.4269/ajtmh.2012.11-0472