Spatio-temporal distribution characteristics of the risk of viral hepatitis B incidence based on INLA in 14 prefectures of Xinjiang from 2004 to 2019

Yijia Wang; Na Xie; Zhe Wang; Shuzhen Ding; Xijian Hu; Kai Wang; Yijia Wang; Na Xie; Zhe Wang; Shuzhen Ding; Xijian Hu; Kai Wang

doi:10.3934/mbe.2023473

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 6: 10678-10693. doi: 10.3934/mbe.2023473

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Spatio-temporal distribution characteristics of the risk of viral hepatitis B incidence based on INLA in 14 prefectures of Xinjiang from 2004 to 2019

1.
College of Mathematics and System Science, Xinjiang University, Urumqi 830017, China
2.
Xinjiang Center for Disease Control and Prevention, Urumqi 830054, China
3.
Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
4.
College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830017, China

Academic Editor: Sen Pei
^† These authors contributed equally

Received: 05 December 2022 Revised: 18 March 2023 Accepted: 24 March 2023 Published: 14 April 2023

This study aimed to explore the spatio-temporal distribution characteristics and risk factors of hepatitis B (HB) in 14 prefectures of Xinjiang, China, and to provide a relevant reference basis for the prevention and treatment of HB. Based on HB incidence data and risk factor indicators in 14 prefectures in Xinjiang from 2004 to 2019, we explored the distribution characteristics of the risk of HB incidence using global trend analysis and spatial autocorrelation analysis and established a Bayesian spatiotemporal model to identify the risk factors of HB and their spatio-temporal distribution to fit and extrapolate the Bayesian spatiotemporal model using the Integrated Nested Laplace Approximation (INLA) method. There was spatial autocorrelation in the risk of HB and an overall increasing trend from west to east and north to south. The natural growth rate, per capita GDP, number of students, and number of hospital beds per 10, 000 people were all significantly associated with the risk of HB incidence. From 2004 to 2019, the risk of HB increased annually in 14 prefectures in Xinjiang, with Changji Hui Autonomous Prefecture, Urumqi City, Karamay City, and Bayangol Mongol Autonomous Prefecture having the highest rates.
- hepatitis B,
- Bayesian spatiotemporal model,
- INLA method,
- risk factor
Citation: Yijia Wang, Na Xie, Zhe Wang, Shuzhen Ding, Xijian Hu, Kai Wang. Spatio-temporal distribution characteristics of the risk of viral hepatitis B incidence based on INLA in 14 prefectures of Xinjiang from 2004 to 2019[J]. Mathematical Biosciences and Engineering, 2023, 20(6): 10678-10693. doi: 10.3934/mbe.2023473

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Abstract

This study aimed to explore the spatio-temporal distribution characteristics and risk factors of hepatitis B (HB) in 14 prefectures of Xinjiang, China, and to provide a relevant reference basis for the prevention and treatment of HB. Based on HB incidence data and risk factor indicators in 14 prefectures in Xinjiang from 2004 to 2019, we explored the distribution characteristics of the risk of HB incidence using global trend analysis and spatial autocorrelation analysis and established a Bayesian spatiotemporal model to identify the risk factors of HB and their spatio-temporal distribution to fit and extrapolate the Bayesian spatiotemporal model using the Integrated Nested Laplace Approximation (INLA) method. There was spatial autocorrelation in the risk of HB and an overall increasing trend from west to east and north to south. The natural growth rate, per capita GDP, number of students, and number of hospital beds per 10, 000 people were all significantly associated with the risk of HB incidence. From 2004 to 2019, the risk of HB increased annually in 14 prefectures in Xinjiang, with Changji Hui Autonomous Prefecture, Urumqi City, Karamay City, and Bayangol Mongol Autonomous Prefecture having the highest rates.

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