Scholarlink

Background <p><i>Clonorchis sinensis</i>, the liver fluke responsible for clonorchiosis, presents a persistent public health burden in Guangxi (Southern China) and Vietnam. Its transmission is influenced by a complex interplay of ecological, climatic, and socio-cultural factors.</p> Methods <p>We compiled infection occurrence data from systematic literature reviews and national surveys conducted between 2000 and 2018. Environmental and climatic predictors were obtained from long-term raster datasets. Machine learning models, including logistic regression and tree-based ensemble methods, were used to assess associations between predictor variables and <i>C. sinensis</i> presence. Partial dependence plots were employed to refine predictor selection and explore marginal effects.</p> Results <p>Raw freshwater fish consumption was identified as the most influential predictor. In Guangxi, 54.9% of counties reported raw fish consumption, compared to 31.7% in Vietnam. Logistic regression achieved the highest predictive accuracy (AUC = 0.941). Climatic comparisons showed that Vietnam had a higher annual mean temperature (Bio1: 23.37&#xa0;°C vs. 20.86&#xa0;°C), greater temperature seasonality (Bio4: 609.33 vs. 464.92), and higher annual precipitation (Bio12: 1731.64&#xa0;mm vs. 1607.56&#xa0;mm) than Guangxi, contributing to spatial differences in endemicity. High-risk zones were concentrated along the China–Vietnam border, suggesting the need for geographically targeted interventions.</p> Conclusion <p>The findings underscore the combined influence of ecological and behavioral factors on <i>C. sinensis</i> transmission. The predictive modeling framework offers valuable insights for surveillance planning and cross-border disease control, reinforcing the role of ecological epidemiology in guiding parasitic disease prevention strategies.</p> Graphical Abstract <p></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

Ecological epidemiology insights into clonorchiosis endemicity in Guangxi, China and Vietnam: a comprehensive machine learning analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月28日

查看全文
  • Jin-Xin Zheng,
  • Hui‐Hui Zhu,
  • Shang Xia,
  • Men‐Bao Qian,
  • Robert Bergquist,
  • Hung Manh Nguyen,
  • Xiao‐Nong Zhou

摘要

Background

Clonorchis sinensis, the liver fluke responsible for clonorchiosis, presents a persistent public health burden in Guangxi (Southern China) and Vietnam. Its transmission is influenced by a complex interplay of ecological, climatic, and socio-cultural factors.

Methods

We compiled infection occurrence data from systematic literature reviews and national surveys conducted between 2000 and 2018. Environmental and climatic predictors were obtained from long-term raster datasets. Machine learning models, including logistic regression and tree-based ensemble methods, were used to assess associations between predictor variables and C. sinensis presence. Partial dependence plots were employed to refine predictor selection and explore marginal effects.

Results

Raw freshwater fish consumption was identified as the most influential predictor. In Guangxi, 54.9% of counties reported raw fish consumption, compared to 31.7% in Vietnam. Logistic regression achieved the highest predictive accuracy (AUC = 0.941). Climatic comparisons showed that Vietnam had a higher annual mean temperature (Bio1: 23.37 °C vs. 20.86 °C), greater temperature seasonality (Bio4: 609.33 vs. 464.92), and higher annual precipitation (Bio12: 1731.64 mm vs. 1607.56 mm) than Guangxi, contributing to spatial differences in endemicity. High-risk zones were concentrated along the China–Vietnam border, suggesting the need for geographically targeted interventions.

Conclusion

The findings underscore the combined influence of ecological and behavioral factors on C. sinensis transmission. The predictive modeling framework offers valuable insights for surveillance planning and cross-border disease control, reinforcing the role of ecological epidemiology in guiding parasitic disease prevention strategies.

Graphical Abstract