ISSN 1003-8280 CN 10-1522/R 中国疾病预防控制中心 主办
Chinese Journal of Vector Biology and Control >
Application of autoregressive integrated moving average model in prediction of hemorrhagic fever with renal syndrome
Received date: 2014-01-10
Online published: 2014-06-20
Objective To evaluate the application of autoregressive integrated moving average (ARIMA) model in the prediction of monthly incidence of hemorrhagic fever with renal syndrome (HFRS). Methods The database of monthly epidemic situation of HFRS in Hebei province, China from 1986 to 2011 was constructed with SPSS 16.0. A mathematic model was constructed using ARIMA of SPSS 16.0 and used to predict the epidemic situation in 2012. Results The HFRS incidence presented obvious seasonal periodicity during 1986 to 2011 in Hebei province. ARIMA (0, 1, 1)×(0, 1, 2)12 model best fitted the incidence of HFRS from January 1986 to December 2011. The actual average incidence of HFRS in 2012 fell within the 95% confidence interval of prediction. Conclusion ARIMA model fits well in the prediction of HFRS incidence, and is suitable for use in epidemiological prediction to provide a basis for the prevention and control of HFRS.
WEI Ya-mei, GUO Na-na, HAN Xu, HAN Zhan-ying, ZHANG Yan-bo, QI Shun-xiang, LI Qi . Application of autoregressive integrated moving average model in prediction of hemorrhagic fever with renal syndrome[J]. Chinese Journal of Vector Biology and Control, 2014 , 25(3) : 231 -234 . DOI: 10.11853/j.issn.1003.4692.2014.03.010
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