Scholarlink

<p>Hepatitis B virus (HBV) infection remains a persistent public health challenge in China, with significant spatiotemporal heterogeneity in incidence. This study aimed to examine regional disparities in hepatitis B incidence, explore its spatiotemporal evolution patterns, and analyze the spatiotemporal heterogeneity of associated factors across China, using incidence data from 2008 to 2023. The Dagum Gini coefficient decomposition method assessed regional disparity sources, the standard deviation ellipse explored spatiotemporal direction and global characteristics, exploratory spatial data analysis (ESDA) examined spatial correlation and aggregation, and the geographically and temporally weighted regression (GTWR) model was used to examine spatiotemporal heterogeneity of influencing factors. Results showed narrowing regional disparities, declining spatial aggregation, and a standard deviation ellipse located in eastern and central regions with a southeastward shift, alongside the incidence gravity center moving 351.25&#xa0;km southeast. Patterns shifted from clustered to dispersed, likely due to vaccination and improved healthcare allocation. Six socioeconomic factors exerted significant yet spatiotemporally heterogeneous impacts, with diverse, regionally varying effects based on economic and policy contexts.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Spatiotemporal evolution characteristics and influencing factors of hepatitis B incidence rate in China

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月22日

查看全文
  • Ke Sun,
  • Siqi Zhang,
  • Fang Wang,
  • Liqing Li

摘要

Hepatitis B virus (HBV) infection remains a persistent public health challenge in China, with significant spatiotemporal heterogeneity in incidence. This study aimed to examine regional disparities in hepatitis B incidence, explore its spatiotemporal evolution patterns, and analyze the spatiotemporal heterogeneity of associated factors across China, using incidence data from 2008 to 2023. The Dagum Gini coefficient decomposition method assessed regional disparity sources, the standard deviation ellipse explored spatiotemporal direction and global characteristics, exploratory spatial data analysis (ESDA) examined spatial correlation and aggregation, and the geographically and temporally weighted regression (GTWR) model was used to examine spatiotemporal heterogeneity of influencing factors. Results showed narrowing regional disparities, declining spatial aggregation, and a standard deviation ellipse located in eastern and central regions with a southeastward shift, alongside the incidence gravity center moving 351.25 km southeast. Patterns shifted from clustered to dispersed, likely due to vaccination and improved healthcare allocation. Six socioeconomic factors exerted significant yet spatiotemporally heterogeneous impacts, with diverse, regionally varying effects based on economic and policy contexts.