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

Spatio-temporal distribution characteristics of the risk of viral hepatitis B incidence based on INLA in 14 prefectures of Xinjiang from 2004 to 2019.
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DOI：
10.3934/mbe.2023473
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发表时间：
2023-04
期刊：
Mathematical biosciences and engineering : MBE
影响因子：
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通讯作者：
Yijia Wang;N. Xie;Zhe Wang;Shuzhen Ding;Xijian Hu;Kai Wang
Yijia Wang;N. Xie;Zhe Wang;Shuzhen Ding;Xijian Hu;Kai Wang
中科院分区：
其他
文献类型：
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作者：
Yijia Wang;N. Xie;Zhe Wang;Shuzhen Ding;Xijian Hu;Kai Wang

文献摘要

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目的探讨新疆14个地州市B型肝炎（HB）的时空分布特征及其危险因素，为HB的防治提供相关参考依据。基于新疆14个地州2004 - 2019年乙肝发病数据和危险因素指标，采用全球趋势分析和空间自相关分析方法，探讨了乙肝发病风险的分布特征，并建立了贝叶斯时空模型，识别乙肝发病的危险因素及其空间分布。时间分布，以使用集成嵌套拉普拉斯逼近（INLA）方法拟合和外推贝叶斯时空模型。乙肝发病风险存在空间自相关性，总体上呈现由西向东、由北向南递增的趋势。自然增长率、人均GDP、在校学生人数、每万人医院床位数与乙肝发病风险显著相关。从2004年到2019年，新疆14个地州的乙肝风险逐年增加，其中昌吉回族自治州、乌鲁木齐市、克拉玛依市和巴彦郭尔蒙古自治州的发病率最高。
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.