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Seasonality and Trend Forecasting of Tuberculosis Incidence in Chongqing, China.
Interdiscip Sci. 2019 Mar; 11(1):77-85.IS

Abstract

Tuberculosis (TB) is a global infectious disease and one of the ten leading causes of death worldwide. As TB incidence is seasonal, a reliable forecasting model that incorporates both seasonal and trend effects would be useful to improve the prevention and control of TB. In this study, the X12 autoregressive integrated moving average (X12-ARIMA) model was constructed by dividing the sequence into season term and trend term to forecast the two terms, respectively. Data regarding the TB report rate from January 2004 to December 2015 were included in the model, and the TB report data from January 2016 to December 2016 were used to validate the results. The X12-ARIMA model was compared with the seasonal autoregressive integrated moving average (SARIMA) model. A total of 383,797 cases were reported from January 2004 to December 2016 in Chongqing, China. The report rate of TB was highest in 2005 (151.06 per 100,000 population) and lowest in 2016 (72.58 per 100,000 population). The final X12-ARIMA model included the ARIMA (3,1,3) model for the trend term and the ARIMA (2,1,3) model for the season term. The SARIMA (1,0,2) * (1,1,1)12 model was selected for the SARIMA model. The mean absolute error (MAE) and mean absolute percentage error (MAPE) of fitting and predicting performance based on the X12-ARIMA model were less than the SARIMA model. In conclusion, the occurrence of TB in Chongqing is controlled, which may be attributed to socioeconomic developments and improved TB prevention and control services. Applying the X12-ARIMA model is an effective method to forecast and analyze the trend and seasonality of TB.

Authors+Show Affiliations

Department of Respiratory, Children's Hospital of Chongqing Medical University, Chongqing, 40010, People's Republic of China.College of Stomatology, Chongqing Medical University, 40016, Chongqing, People's Republic of China.Medicine Engineering Research Center, College of Pharmacy, Chongqing Medical University, Chongqing, 40016, People's Republic of China.Department of Respiratory, Children's Hospital of Chongqing Medical University, Chongqing, 40010, People's Republic of China. gangwanvi@163.com.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

30734907

Citation

Liao, Zhaoying, et al. "Seasonality and Trend Forecasting of Tuberculosis Incidence in Chongqing, China." Interdisciplinary Sciences, Computational Life Sciences, vol. 11, no. 1, 2019, pp. 77-85.
Liao Z, Zhang X, Zhang Y, et al. Seasonality and Trend Forecasting of Tuberculosis Incidence in Chongqing, China. Interdiscip Sci. 2019;11(1):77-85.
Liao, Z., Zhang, X., Zhang, Y., & Peng, D. (2019). Seasonality and Trend Forecasting of Tuberculosis Incidence in Chongqing, China. Interdisciplinary Sciences, Computational Life Sciences, 11(1), 77-85. https://doi.org/10.1007/s12539-019-00318-x
Liao Z, et al. Seasonality and Trend Forecasting of Tuberculosis Incidence in Chongqing, China. Interdiscip Sci. 2019;11(1):77-85. PubMed PMID: 30734907.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Seasonality and Trend Forecasting of Tuberculosis Incidence in Chongqing, China. AU - Liao,Zhaoying, AU - Zhang,Xiaonan, AU - Zhang,Yonghong, AU - Peng,Donghong, Y1 - 2019/02/08/ PY - 2018/11/11/received PY - 2019/01/09/accepted PY - 2019/01/07/revised PY - 2019/2/9/pubmed PY - 2019/6/27/medline PY - 2019/2/9/entrez KW - Prediction model KW - Seasonality KW - Tuberculosis control KW - Tuberculosis incidence SP - 77 EP - 85 JF - Interdisciplinary sciences, computational life sciences JO - Interdiscip Sci VL - 11 IS - 1 N2 - Tuberculosis (TB) is a global infectious disease and one of the ten leading causes of death worldwide. As TB incidence is seasonal, a reliable forecasting model that incorporates both seasonal and trend effects would be useful to improve the prevention and control of TB. In this study, the X12 autoregressive integrated moving average (X12-ARIMA) model was constructed by dividing the sequence into season term and trend term to forecast the two terms, respectively. Data regarding the TB report rate from January 2004 to December 2015 were included in the model, and the TB report data from January 2016 to December 2016 were used to validate the results. The X12-ARIMA model was compared with the seasonal autoregressive integrated moving average (SARIMA) model. A total of 383,797 cases were reported from January 2004 to December 2016 in Chongqing, China. The report rate of TB was highest in 2005 (151.06 per 100,000 population) and lowest in 2016 (72.58 per 100,000 population). The final X12-ARIMA model included the ARIMA (3,1,3) model for the trend term and the ARIMA (2,1,3) model for the season term. The SARIMA (1,0,2) * (1,1,1)12 model was selected for the SARIMA model. The mean absolute error (MAE) and mean absolute percentage error (MAPE) of fitting and predicting performance based on the X12-ARIMA model were less than the SARIMA model. In conclusion, the occurrence of TB in Chongqing is controlled, which may be attributed to socioeconomic developments and improved TB prevention and control services. Applying the X12-ARIMA model is an effective method to forecast and analyze the trend and seasonality of TB. SN - 1867-1462 UR - https://www.unboundmedicine.com/medline/citation/30734907/Seasonality_and_Trend_Forecasting_of_Tuberculosis_Incidence_in_Chongqing_China_ L2 - https://dx.doi.org/10.1007/s12539-019-00318-x DB - PRIME DP - Unbound Medicine ER -
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