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

Zheng YL, Zhang LP, Zhang XL, Wang K, Zheng YJ - PLoS ONE (2015)

Bottom Line: 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.Comparative analyses show that the combined model is more effective.

View Article: PubMed Central - PubMed

Affiliation: College of Public Health, Xinjiang Medical University, Urumqi, 830011, People's Republic of China; College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, 830011, People's Republic of China.

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 establish the ARIMA model and ARIMA-ARCH model for prediction and monitoring the monthly morbidity of tuberculosis in Xinjiang. Based on the results of this study, the ARIMA (1, 1, 2) (1, 1, 1)12-ARCH (1) model is suggested to give tuberculosis surveillance by providing estimates on tuberculosis morbidity trends in Xinjiang, China.

Show MeSH

Related in: MedlinePlus

The annual morbidity of tuberculosis from 2008 to 2012 in Xinjiang and in China.Xinjiang is one of the autonomous regions of China; its morbidity of tuberculosis (TB) is much higher than the national situation.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4356615&req=5

pone.0116832.g001: The annual morbidity of tuberculosis from 2008 to 2012 in Xinjiang and in China.Xinjiang is one of the autonomous regions of China; its morbidity of tuberculosis (TB) is much higher than the national situation.

Mentions: The Xinjiang Uygur Autonomous Region is located in the northwestern border of China; its area is 1.66 million square kilometers, accounting for 1/6 of total area of China, it is the largest autonomous region of China [2]. Its morbidity of TB is much higher than the national situation as shown in Fig. 1. According to the fifth TB epidemiology survey in Xinjiang in 2010, some people over the age of 15 suffered from active pulmonary TB, and the morbidity was 1525 (per 100,000 population), which was 3.32 times higher than the TB morbidity of whole country, the number of active pulmonary TB patients was more than 260,000 [3]. In the last ten years, compared with other infectious disease prevalence, the morbidity of TB has always been ranked in the top two in Xinjiang. This disease is a serious public health and social problem affecting economic and social development, its prevention and control has been signaled as being of great importance: Establishing the accurate morbidity prediction model of TB forecasts future epidemic situation, which can provide scientific basis for formulating the correct control planning.


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

Zheng YL, Zhang LP, Zhang XL, Wang K, Zheng YJ - PLoS ONE (2015)

The annual morbidity of tuberculosis from 2008 to 2012 in Xinjiang and in China.Xinjiang is one of the autonomous regions of China; its morbidity of tuberculosis (TB) is much higher than the national situation.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4356615&req=5

pone.0116832.g001: The annual morbidity of tuberculosis from 2008 to 2012 in Xinjiang and in China.Xinjiang is one of the autonomous regions of China; its morbidity of tuberculosis (TB) is much higher than the national situation.
Mentions: The Xinjiang Uygur Autonomous Region is located in the northwestern border of China; its area is 1.66 million square kilometers, accounting for 1/6 of total area of China, it is the largest autonomous region of China [2]. Its morbidity of TB is much higher than the national situation as shown in Fig. 1. According to the fifth TB epidemiology survey in Xinjiang in 2010, some people over the age of 15 suffered from active pulmonary TB, and the morbidity was 1525 (per 100,000 population), which was 3.32 times higher than the TB morbidity of whole country, the number of active pulmonary TB patients was more than 260,000 [3]. In the last ten years, compared with other infectious disease prevalence, the morbidity of TB has always been ranked in the top two in Xinjiang. This disease is a serious public health and social problem affecting economic and social development, its prevention and control has been signaled as being of great importance: Establishing the accurate morbidity prediction model of TB forecasts future epidemic situation, which can provide scientific basis for formulating the correct control planning.

Bottom Line: 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.Comparative analyses show that the combined model is more effective.

View Article: PubMed Central - PubMed

Affiliation: College of Public Health, Xinjiang Medical University, Urumqi, 830011, People's Republic of China; College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, 830011, People's Republic of China.

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 establish the ARIMA model and ARIMA-ARCH model for prediction and monitoring the monthly morbidity of tuberculosis in Xinjiang. Based on the results of this study, the ARIMA (1, 1, 2) (1, 1, 1)12-ARCH (1) model is suggested to give tuberculosis surveillance by providing estimates on tuberculosis morbidity trends in Xinjiang, China.

Show MeSH
Related in: MedlinePlus