Time series analysis for forecasting model of tuberculosis in schools
10.3969/j.issn.1006-2483.2022.05.025
- VernacularTitle:学校结核病时间序列分析及预测模型研究
- Author:
Li LI
1
;
Yi-xin LIU
1
;
Yun YANG
1
;
Jing LIU
1
;
Li-na WANG
2
Author Information
1. Hongshan District Center for Disease Control and Prevention , Wuhan , Hubei 430064 , China
2. School of Computer and Communication Engineering , Zhengzhou University of Light Industry , Zhengzhou , Henan 450001 , China
- Publication Type:Journal Article
- Keywords:
Students;
Tuberculosis;
Time series;
Forecasting
- From:
Journal of Public Health and Preventive Medicine
2022;33(5):106-110
- CountryChina
- Language:Chinese
-
Abstract:
Objective To establish early forecasting model of tuberculosis in schools of Hongshan district, and provide scientific strategy for prevention and control of tuberculosis. Methods Using data on 2013-2020 in schools tuberculosis, established time series models and chosen the best one to forecast and tested the incidence of tuberculosis. Results The best model for school tuberculosis was ARIMA (0,0,3) (0,1,1)12. The trend of the predicted value was basically consistent with the actual value which was also in the 95% confidence interval of predicted numbers. The effectiveness of forecasting was good with a 2.313% value of MAPE. Conclusion The ARIMA product seasonal model can effectively fit and forecast time series data on students'’ tuberculosis. It also can be used to early warn and predict the incidence of school tuberculosis in Hongshan district.
