ARIMA乘积季节模型在青州市布鲁氏菌病发病预测中的应用

doi:10.3969/j.issn.1006-5253.2020.02.001

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Abstract Objective To predict the monthly incidence of brucellosis in Qingzhou by multiple seasonal ARIMA model of autoregressive integrated moving average (ARIMA), and to construct a prediction model for the monthly incidence of brucellosis in Qingzhou so as to provide scientific basis for prevention and control measures of brucellosis in Qingzhou. Methods The monitoring data of brucellosis in Qingzhou from 2011 to 2017 were collected, ARIMA time series model was established with SPSS 25.0 statistical software, the model was tested to predict the monthly incidence of brucellosis in 2018, and the prediction effect of the model was evaluated by the actual monthly incidence of brucellosis in 2018. Results The normalized BIC value of ARIMA(0,1,1)(1,1,0)₁₂model is the smallest, the Box-Ljung test statistic is as follows: Q=23.746, P>0.05, the residual sequence is white noise, thus it is determined to be the optimal model. Conclusion Multiple seasonal ARIMA model is effective in short-term prediction of monthly incidence of brucellosis in Qingzhou.

Key words： ARIMA model brucellosis monthly incidence forecast

Received: 26 October 2019

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	Articles by authors
	Liu Jie1
	Wu Qinfa
	Li Weiguo
	Xiao Yufei
	Mao Qian
	Shi Fuyan
	Wang Suzhen.

Cite this article:

Liu Jie1,Wu Qinfa,Li Weiguo, et al. Application of multiple seasonal ARIMA model in forecasting the incidence of brucellosis in Qingzhou[J]. journal1, 2020, 27(2): 97-100.

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http://manu58.magtech.com.cn/Jwk_zgyytj/EN/10.3969/j.issn.1006-5253.2020.02.001 OR http://manu58.magtech.com.cn/Jwk_zgyytj/EN/Y2020/V27/I2/97

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