Hepatitis B time series in Xinjiang, China (2006–2021): change point detection based on the Mann-Kendall-Sneyers test

Liping Yang; Na Xie; Yanru Yao; Chunxia Wang; Maozai Tian; Kai Wang; Liping Yang; Na Xie; Yanru Yao; Chunxia Wang; Maozai Tian; Kai Wang

doi:10.3934/mbe.2024108

Mathematical Biosciences and Engineering

2024, Volume 21, Issue 2: 2458-2469. doi: 10.3934/mbe.2024108

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Research article

Hepatitis B time series in Xinjiang, China (2006–2021): change point detection based on the Mann-Kendall-Sneyers test

1.
College of Public Health, Xinjiang Medical University, Urumqi 830017, China
2.
Department of Immunization Programme, Xinjiang Center for Disease Control and Prevention, Urumqi 830054, China
3.
College of Science, Shihezi University, Shihezi 832000, China
4.
College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830017, China

Received: 08 August 2023 Revised: 20 November 2023 Accepted: 27 December 2023 Published: 17 January 2024

Hepatitis B is a major global challenge, but there is a lack of epidemiological research on hepatitis B incidence from a change point perspective. This study aimed to fill this gap by identifying significant change points and trends in hepatitis time series in Xinjiang, China. The datasets were obtained from the Xinjiang Information System for Disease Control and Prevention. The Mann-Kendall-Sneyers (MKS) test was used to detect change points and trend changes on the hepatitis B time series of 14 regions in Xinjiang, and the effectiveness of this method was validated by comparing it with the binary segmentation (BS) and segment regression (SR) methods. Based on the results of change point analysis, the prevention and control policies and measures of hepatitis in Xinjiang were discussed. The results showed that 8 regions (57.1%) with at least one change fell within the 95% confidence interval (CI) in all 14 regions by the MKS test, where five regions (Turpan (TP), Hami (HM), Bayingolin (BG), Kyzylsu Kirgiz (KK), Altai (AT)) were identified at one change point, two change points existed for two regions (Aksu (AK), Hotan (HT)) and three change points was detected in 1 region (Bortala (BT)). Most of the change points occurred at both ends of the sequence. More change points indicated an upward trend in the front half of the sequence, while in the latter half, many change points indicated a downward trend prominently. Finally, in comparing the results of the three change point tests, the MKS test showed a 61.5% agreement (8/13) with the BS and SR.
- Hepatitis B,
- Change point,
- the MKS test,
- BS,
- SR
Citation: Liping Yang, Na Xie, Yanru Yao, Chunxia Wang, Maozai Tian, Kai Wang. Hepatitis B time series in Xinjiang, China (2006–2021): change point detection based on the Mann-Kendall-Sneyers test[J]. Mathematical Biosciences and Engineering, 2024, 21(2): 2458-2469. doi: 10.3934/mbe.2024108

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Abstract

Hepatitis B is a major global challenge, but there is a lack of epidemiological research on hepatitis B incidence from a change point perspective. This study aimed to fill this gap by identifying significant change points and trends in hepatitis time series in Xinjiang, China. The datasets were obtained from the Xinjiang Information System for Disease Control and Prevention. The Mann-Kendall-Sneyers (MKS) test was used to detect change points and trend changes on the hepatitis B time series of 14 regions in Xinjiang, and the effectiveness of this method was validated by comparing it with the binary segmentation (BS) and segment regression (SR) methods. Based on the results of change point analysis, the prevention and control policies and measures of hepatitis in Xinjiang were discussed. The results showed that 8 regions (57.1%) with at least one change fell within the 95% confidence interval (CI) in all 14 regions by the MKS test, where five regions (Turpan (TP), Hami (HM), Bayingolin (BG), Kyzylsu Kirgiz (KK), Altai (AT)) were identified at one change point, two change points existed for two regions (Aksu (AK), Hotan (HT)) and three change points was detected in 1 region (Bortala (BT)). Most of the change points occurred at both ends of the sequence. More change points indicated an upward trend in the front half of the sequence, while in the latter half, many change points indicated a downward trend prominently. Finally, in comparing the results of the three change point tests, the MKS test showed a 61.5% agreement (8/13) with the BS and SR.

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