Retrospective Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Nov 14, 2023; 29(42): 5716-5727
Published online Nov 14, 2023. doi: 10.3748/wjg.v29.i42.5716
Time series analysis-based seasonal autoregressive fractionally integrated moving average to estimate hepatitis B and C epidemics in China
Yong-Bin Wang, Si-Yu Qing, Zi-Yue Liang, Chang Ma, Yi-Chun Bai, Chun-Jie Xu
Yong-Bin Wang, Si-Yu Qing, Zi-Yue Liang, Chang Ma, Yi-Chun Bai, Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang 453003, Henan Province, China
Chun-Jie Xu, Beijing Key Laboratory of Antimicrobial Agents/Laboratory of Pharmacology, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100010, China
Author contributions: Wang YB conceived, initiated, and performed this work; Qing SY, Ma C, Liang ZY, Bai YC, and Xu CJ collected, analyzed, and interpreted the data for this study; Wang YB, Qing SY, Liang ZY, Bai YC, Xu CJ, and Ma C edited and improved this original manuscript; all authors reviewed and approved the manuscript.
Supported by the Key Scientific Research Project of Universities in Henan Province, No. 21A330004; and Natural Science Foundation in Henan Province, No. 222300420265.
Institutional review board statement: This study was reviewed and approved by the institutional review board of Xinxiang Medical University (No: XYLL-2019072). All methods were carried out under relevant guidelines and regulations.
Informed consent statement: The need for informed consent was waived by the Ethics Committee of Xinxiang Medical University because the HB and HC cases were shared anonymously and we cannot access any identifying information of the patients (available from: https://www.phsciencedata.cn/Share/).
Conflict-of-interest statement: We have no financial relationships to disclose.
Data sharing statement: All the data supporting the findings of the work are contained within the study or technical appendix, statistical code, and dataset available from the corresponding author at 191035@xxmu.edu.cn.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Yong-Bin Wang, MD, Researcher, Teacher, Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, No. 601 Jinsui Road, Hongqi District, Xinxiang 453003, Henan Province, China. 191035@xxmu.edu.cn
Received: August 5, 2023
Peer-review started: August 5, 2023
First decision: September 18, 2023
Revised: September 28, 2023
Accepted: October 23, 2023
Article in press: October 23, 2023
Published online: November 14, 2023
Processing time: 97 Days and 21.1 Hours
Abstract
BACKGROUND

Hepatitis B (HB) and hepatitis C (HC) place the largest burden in China, and a goal of eliminating them as a major public health threat by 2030 has been set. Making more informed and accurate forecasts of their spread is essential for developing effective strategies, heightening the requirement for early warning to deal with such a major public health threat.

AIM

To monitor HB and HC epidemics by the design of a paradigmatic seasonal autoregressive fractionally integrated moving average (SARFIMA) for projections into 2030, and to compare the effectiveness with the seasonal autoregressive integrated moving average (SARIMA).

METHODS

Monthly HB and HC incidence cases in China were obtained from January 2004 to June 2023. Descriptive analysis and the Hodrick-Prescott method were employed to identify trends and seasonality. Two periods (from January 2004 to June 2022 and from January 2004 to December 2015, respectively) were used as the training sets to develop both models, while the remaining periods served as the test sets to evaluate the forecasting accuracy.

RESULTS

There were incidents of 23400874 HB cases and 3590867 HC cases from January 2004 to June 2023. Overall, HB remained steady [average annual percentage change (AAPC) = 0.44, 95% confidence interval (95%CI): -0.94-1.84] while HC was increasing (AAPC = 8.91, 95%CI: 6.98-10.88), and both had a peak in March and a trough in February. In the 12-step-ahead HB forecast, the mean absolute deviation (15211.94), root mean square error (18762.94), mean absolute percentage error (0.17), mean error rate (0.15), and root mean square percentage error (0.25) under the best SARFIMA (3, 0, 0) (0, 0.449, 2)12 were smaller than those under the best SARIMA (3, 0, 0) (0, 1, 2)12 (16867.71, 20775.12, 0.19, 0.17, and 0.27, respectively). Similar results were also observed for the 90-step-ahead HB, 12-step-ahead HC, and 90-step-ahead HC forecasts. The predicted HB incidents totaled 9865400 (95%CI: 7508093-12222709) cases and HC totaled 1659485 (95%CI: 856681-2462290) cases during 2023-2030.

CONCLUSION

Under current interventions, China faces enormous challenges to eliminate HB and HC epidemics by 2030, and effective strategies must be reinforced. The integration of SARFIMA into public health for the management of HB and HC epidemics can potentially result in more informed and efficient interventions, surpassing the capabilities of SARIMA.

Keywords: Hepatitis; Seasonal autoregressive fractionally integrated moving average; Seasonal autoregressive integrated moving average; Prediction; Epidemic; Time series analysis

Core Tip: This retrospective study used a seasonal autoregressive fractionally integrated moving average (SARFIMA) to monitor hepatitis B (HB) and hepatitis C (HC) epidemics, and its forecasting potential was then compared to that of the seasonal autoregressive integrated moving average (ARIMA) (SARIMA). The resulting forecast error rates under the SARFIMA were less than those under the SARIMA. The integration of SARFIMA into public health decision-making for the management of HB and HC epidemics can result in more informed interventions. The predicted HB totaled 9865400 [95% confidence interval (95%CI): 7508093-12222709] cases and HC totaled 1659485 (95%CI: 856681-2462290) cases in 2030, resulting in major challenges to eliminate hepatitis in China by 2030.