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Comparison of ARIMA and GM(1,1) models for prediction of hepatitis B in China.
PLoS One. 2018; 13(9):e0201987.Plos

Abstract

BACKGROUND

Hepatitis B virus (HBV) infection is a major public health threat in China for China has a hepatitis B prevalence of more than one million people in 2017 year. Disease incidence prediction may help hepatitis B prevention and control. This study intends to build and compare 2 forecasting models for hepatitis B incidence in China.

METHODS

Autoregressive integrated moving average (ARIMA) model and grey model GM(1,1) were adopted to fit the monthly incidence of hepatitis B in China from March 2010 to October 2017. The fitting and forecasting performances of the 2 models were evaluated. The better one was adopted to predict the incidence from November 2017 to March 2018. Database was built by Excel 2016 and statistical analysis was completed using R 3.4.3 software.

RESULTS

Descriptive analysis showed that the incidence of hepatitis B in China has seasonal variation and has shown a downward trend from 2010 to 2017. We selected the ARIMA (3,1,1) (0,1,2)12 model among all the ARIMA models for it has the lowest AIC value. Model expression of GM (1,1) was X(1) (k + 1) = 3386876.7478e0.0249k - 3289206.7428. The root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of ARIMA(3,1,1)(0,1,2)12 model were lower than GM(1,1) model on fitting part and forecasting part. According to the forecast results, the incidence may have a slight fluctuation during the following months.

CONCLUSIONS

The ARIMA model showed better hepatitis B fitting and forecasting performance than GM(1,1) model. It is a potential decision supportive tool for controlling hepatitis B in China before a predictive hepatitis B outbreak.

Authors+Show Affiliations

School of Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.School of Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.School of Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.

Pub Type(s)

Comparative Study
Journal Article

Language

eng

PubMed ID

30180159

Citation

Wang, Ya-Wen, et al. "Comparison of ARIMA and GM(1,1) Models for Prediction of Hepatitis B in China." PloS One, vol. 13, no. 9, 2018, pp. e0201987.
Wang YW, Shen ZZ, Jiang Y. Comparison of ARIMA and GM(1,1) models for prediction of hepatitis B in China. PLoS ONE. 2018;13(9):e0201987.
Wang, Y. W., Shen, Z. Z., & Jiang, Y. (2018). Comparison of ARIMA and GM(1,1) models for prediction of hepatitis B in China. PloS One, 13(9), e0201987. https://doi.org/10.1371/journal.pone.0201987
Wang YW, Shen ZZ, Jiang Y. Comparison of ARIMA and GM(1,1) Models for Prediction of Hepatitis B in China. PLoS ONE. 2018;13(9):e0201987. PubMed PMID: 30180159.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Comparison of ARIMA and GM(1,1) models for prediction of hepatitis B in China. AU - Wang,Ya-Wen, AU - Shen,Zhong-Zhou, AU - Jiang,Yu, Y1 - 2018/09/04/ PY - 2018/05/14/received PY - 2018/07/25/accepted PY - 2018/9/5/entrez PY - 2018/9/5/pubmed PY - 2019/2/12/medline SP - e0201987 EP - e0201987 JF - PloS one JO - PLoS ONE VL - 13 IS - 9 N2 - BACKGROUND: Hepatitis B virus (HBV) infection is a major public health threat in China for China has a hepatitis B prevalence of more than one million people in 2017 year. Disease incidence prediction may help hepatitis B prevention and control. This study intends to build and compare 2 forecasting models for hepatitis B incidence in China. METHODS: Autoregressive integrated moving average (ARIMA) model and grey model GM(1,1) were adopted to fit the monthly incidence of hepatitis B in China from March 2010 to October 2017. The fitting and forecasting performances of the 2 models were evaluated. The better one was adopted to predict the incidence from November 2017 to March 2018. Database was built by Excel 2016 and statistical analysis was completed using R 3.4.3 software. RESULTS: Descriptive analysis showed that the incidence of hepatitis B in China has seasonal variation and has shown a downward trend from 2010 to 2017. We selected the ARIMA (3,1,1) (0,1,2)12 model among all the ARIMA models for it has the lowest AIC value. Model expression of GM (1,1) was X(1) (k + 1) = 3386876.7478e0.0249k - 3289206.7428. The root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of ARIMA(3,1,1)(0,1,2)12 model were lower than GM(1,1) model on fitting part and forecasting part. According to the forecast results, the incidence may have a slight fluctuation during the following months. CONCLUSIONS: The ARIMA model showed better hepatitis B fitting and forecasting performance than GM(1,1) model. It is a potential decision supportive tool for controlling hepatitis B in China before a predictive hepatitis B outbreak. SN - 1932-6203 UR - https://www.unboundmedicine.com/medline/citation/30180159/Comparison_of_ARIMA_and_GM_11__models_for_prediction_of_hepatitis_B_in_China_ L2 - http://dx.plos.org/10.1371/journal.pone.0201987 DB - PRIME DP - Unbound Medicine ER -