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Yan CQ, Wang RB, Liu HC, Jiang Y, Li MC, Yin SP, Xiao TY, Wan KL, Rang WQ. [Application of ARIMA model in predicting the incidence of tuberculosis in China from 2018 to 2019]. Zhonghua Liu Xing Bing Xue Za Zhi 2019; 40:633-637. [PMID: 31238610 DOI: 10.3760/cma.j.issn.0254-6450.2019.06.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: Autoregressive integrated moving average (ARIMA) model was used to predict the incidence of tuberculosis in China from 2018 to 2019, providing references for the prevention and control of pulmonary tuberculosis. Methods: The monthly incidence data of tuberculosis in China were collected from January 2005 to December 2017. R 3.4.4 software was used to establish the ARIMA model, based on the monthly incidence data of tuberculosis from January 2005 to June 2017. Both predicted and actual data from July to December 2017 were compared to verify the effectiveness of this model, and the number of tuberculosis cases in 2018-2019 also predicted. Results: From 2005 to 2017, a total of 13 022 675 cases of tuberculosis were reported, the number of pulmonary tuberculosis patients in 2017 was 33.68% lower than that in 2005, and the seasonal character was obvious, with the incidence in winter and spring was higher than that in other seasons. According to the incidence data from 2005 to 2017, we established the model of ARIMA (0,1,2)(0,1,0)(12). The relative error between the predicted and actual values of July to December 2017 fitted by the model ranged from 1.67% to 6.80%, and the predicted number of patients in 2018 and 2019 were 789 509 and 760 165 respectively. Conclusion: The ARIMA (0, 1, 2)(0, 1, 0)(12) model well predicted the incidence of tuberculosis, thus can be used for short-term prediction and dynamic analysis of tuberculosis in China, with good application value.
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Affiliation(s)
- C Q Yan
- School of Public Health, University of South China, Hengyang 421001, China
| | - R B Wang
- State Key Laboratory for Infectious Diseases Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - H C Liu
- State Key Laboratory for Infectious Diseases Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Y Jiang
- State Key Laboratory for Infectious Diseases Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - M C Li
- State Key Laboratory for Infectious Diseases Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - S P Yin
- State Key Laboratory for Infectious Diseases Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - T Y Xiao
- State Key Laboratory for Infectious Diseases Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - K L Wan
- State Key Laboratory for Infectious Diseases Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - W Q Rang
- School of Public Health, University of South China, Hengyang 421001, China
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Xiao YC, Liu LT, Bian JJ, Yan CQ, Ye L, Zhao MX, Huang QS, Wang W, Liang K, Shi ZF, Ke X. Identification of multiple constituents in shuganjieyu capsule and rat plasma after oral administration by ultra-performance liquid chromatography coupled with electrospray ionization and ion trap mass spectrometry. ACTA CHROMATOGR 2018. [DOI: 10.1556/1326.2017.00094] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Y. C. Xiao
- Chengdu Kanghong Pharmaceutical Co. Ltd., Chengdu, Sichuan 610036, P.R. China
| | - L. T. Liu
- Chengdu Kanghong Pharmaceutical Co. Ltd., Chengdu, Sichuan 610036, P.R. China
| | - J. J. Bian
- Chengdu Kanghong Pharmaceutical Co. Ltd., Chengdu, Sichuan 610036, P.R. China
| | - C. Q. Yan
- Chengdu Kanghong Pharmaceutical Co. Ltd., Chengdu, Sichuan 610036, P.R. China
| | - L. Ye
- Chengdu Kanghong Pharmaceutical Co. Ltd., Chengdu, Sichuan 610036, P.R. China
| | - M. X. Zhao
- Chengdu Kanghong Pharmaceutical Co. Ltd., Chengdu, Sichuan 610036, P.R. China
| | - Q. S. Huang
- Chengdu Kanghong Pharmaceutical Co. Ltd., Chengdu, Sichuan 610036, P.R. China
| | - W. Wang
- Chengdu Kanghong Pharmaceutical Co. Ltd., Chengdu, Sichuan 610036, P.R. China
| | - K. Liang
- Chengdu Kanghong Pharmaceutical Co. Ltd., Chengdu, Sichuan 610036, P.R. China
| | - Z. F. Shi
- Chengdu Kanghong Pharmaceutical Co. Ltd., Chengdu, Sichuan 610036, P.R. China
| | - X. Ke
- Chengdu Kanghong Pharmaceutical Co. Ltd., Chengdu, Sichuan 610036, P.R. China
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