Abstract
An analysis and prediction for the incidence of tuberculosis (TB) is particularly important since TB still has a high fatality rate in the world. However, this prediction is often influenced by inaccurate forecasting ways. We used data from 364,762 reported TB cases between January 2005 and December 2015 in Shaanxi Province, China. The known number of cases in 2016 was used to assess the accuracy of the model’s predictions. Through all aspects of analysis and comparison, the ARIMA (0, 1, 2) (0, 1, 1)12 were the most model. In the fitting dataset, for the ARIMA (0, 1, 2) (0, 1, 1)12 model, RMSE, MAPE, MAE and MER were 0.7667, 6.7810, 6.04944 and 0.06836, respectively; And in the forecasting dataset were 0.32808, 6.01834, 0.2899 and 0.0615, respectively. The model can predict the seasonal changes and trends of tuberculosis in the Shaanxi province’s population.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
