Forecast model analysis for the morbidity of tuberculosis in Xinjiang, China

PloS One
Yan-Ling ZhengYu-Jian Zheng

Abstract

Tuberculosis is a major global public health problem, which also affects economic and social development. China has the second largest burden of tuberculosis in the world. The tuberculosis morbidity in Xinjiang is much higher than the national situation; therefore, there is an urgent need for monitoring and predicting tuberculosis morbidity so as to make the control of tuberculosis more effective. Recently, the Box-Jenkins approach, specifically the autoregressive integrated moving average (ARIMA) model, is typically applied to predict the morbidity of infectious diseases; it can take into account changing trends, periodic changes, and random disturbances in time series. Autoregressive conditional heteroscedasticity (ARCH) models are the prevalent tools used to deal with time series heteroscedasticity. In this study, based on the data of the tuberculosis morbidity from January 2004 to June 2014 in Xinjiang, we establish the single ARIMA (1, 1, 2) (1, 1, 1)12 model and the combined ARIMA (1, 1, 2) (1, 1, 1)12-ARCH (1) model, which can be used to predict the tuberculosis morbidity successfully in Xinjiang. Comparative analyses show that the combined model is more effective. To the best of our knowledge, this is the first study to...Continue Reading

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Citations

Dec 23, 2017·Journal of Huazhong University of Science and Technology. Medical Sciences = Hua Zhong Ke Ji Da Xue Xue Bao. Yi Xue Ying De Wen Ban = Huazhong Keji Daxue Xuebao. Yixue Yingdewen Ban·Ying PengXiao-Bing Yang
Aug 1, 2018·International Journal of Environmental Research and Public Health·Sangwon ChaeDonghyun Lee
Apr 24, 2020·BMC Infectious Diseases·Yanling ZhengRamziya Rifhat
Aug 21, 2018·International Journal of Epidemiology·Sandra AlbaCharalampos Sismanidis
Nov 26, 2020·Epidemiology and Infection·Yao WangTianmu Chen
Aug 9, 2021·BMC Infectious Diseases·Lingen ShiGengfeng Fu
Nov 19, 2021··Louie Ville A. BalinoJoseph Ludwin D. C. Marigmen

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