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Canadian Journal of Infectious Diseases and Medical Microbiology
Volume 2019, Article ID 1429462, 9 pages
Research Article

Epidemic Situation of Brucellosis in Jinzhou City of China and Prediction Using the ARIMA Model

1Department of Toxicology, School of Public Health, China Medical University, Shenyang 110122, China
2Jinzhou Centre for Disease Control and Prevention, No. 8-35, Section I, Jiefang Road, Jinzhou 121000, China
3Department of Epidemiology, School of Public Health, China Medical University, Shenyang 110122, China

Correspondence should be addressed to Cuihong Jin; nc.ude.umc@nijhc

Received 21 January 2019; Revised 12 April 2019; Accepted 8 May 2019; Published 13 June 2019

Academic Editor: José A. Oteo

Copyright © 2019 Lulu Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Objective. This study aimed to investigate the specific epidemiological characteristics and epidemic situation of brucellosis in Jinzhou City of China so as to establish a suitable prediction model potentially applied as a decision-supportive tool for reasonably assigning health interventions and health delivery. Methods. Monthly morbidity data from 2004 to 2013 were selected to construct the autoregressive integrated moving average (ARIMA) model using SPSS 13.0 software. Moreover, stability analysis and sequence tranquilization, model recognition, parameter test, and model diagnostic were also carried out. Finally, the fitting and prediction accuracy of the ARIMA model were evaluated using the monthly morbidity data in 2014. Results. A total of 3078 cases affected by brucellosis were reported from January 1998 to December 2015 in Jinzhou City. The incidence of brucellosis had shown a fluctuating growth gradually. Moreover, the ARIMA(1,1,1)(0,1,1)12 model was finally selected among quite a few plausible ARIMA models based upon the parameter test, correlation analysis, and Box–Ljung test. Notably, the incidence from 2005 to 2014 forecasted using this ARIMA model fitted well with the actual incidence data. Notably, the actual morbidity in 2014 fell within the scope of 95% confidence limit of values predicted by the ARIMA(1,1,1)(0,1,1)12 model, with the absolute error between the predicted and the actual values in 2014 ranging from 0.02 to 0.74. Meanwhile, the MAPE was 19.83%. Conclusion. It is suitable to predict the incidence of brucellosis in Jinzhou City of China using the ARIMA(1,1,1)(0,1,1)12 model.