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自然变量将东南亚地区的华支睾吸虫和麝猫后睾吸虫的流行区沿着一条连续的直线分隔开来。

Natural variables separate the endemic areas of Clonorchis sinensis and Opisthorchis viverrini along a continuous, straight zone in Southeast Asia.

机构信息

School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, 20025, China.

One Health Center, Shanghai Jiao Tong University, The University of Edinburgh, Shanghai, 20025, China.

出版信息

Infect Dis Poverty. 2024 Mar 12;13(1):24. doi: 10.1186/s40249-024-01191-7.

Abstract

BACKGROUND

Clonorchiasis and opisthorchiasis, caused by the liver flukes Clonorchis sinensis and Opisthorchis viverrini respectively, represent significant neglected tropical diseases (NTDs) in Asia. The co-existence of these pathogens in overlapping regions complicates effective disease control strategies. This study aimed to clarify the distribution and interaction of these diseases within Southeast Asia.

METHODS

We systematically collated occurrence records of human clonorchiasis (n = 1809) and opisthorchiasis (n = 731) across the Southeast Asia countries. Utilizing species distribution models incorporating environmental and climatic data, coupled machine learning algorithms with boosted regression trees, we predicted and distinguished endemic areas for each fluke species. Machine learning techniques, including geospatial analysis, were employed to delineate the boundaries between these flukes.

RESULTS

Our analysis revealed that the endemic range of C. sinensis and O. viverrini in Southeast Asia primarily spans across part of China, Vietnam, Thailand, Laos, and Cambodia. During the period from 2000 to 2018, we identified C. sinensis infections in 84 distinct locations, predominantly in southern China (Guangxi Zhuang Autonomous Region) and northern Vietnam. In a stark contrast, O. viverrini was more widely distributed, with infections documented in 721 locations across Thailand, Laos, Cambodia, and Vietnam. Critical environmental determinants were quantitatively analyzed, revealing annual mean temperatures ranging between 14 and 20 °C in clonorchiasis-endemic areas and 24-30 °C in opisthorchiasis regions (P < 0.05). The machine learning model effectively mapped a distinct demarcation zone, demonstrating a clear separation between the endemic areas of these two liver flukes with AUC from 0.9 to1. The study in Vietnam delineates the coexistence and geographical boundaries of C. sinensis and O. viverrini, revealing distinct endemic zones and a transitional area where both liver fluke species overlap.

CONCLUSIONS

Our findings highlight the critical role of specific climatic and environmental factors in influencing the geographical distribution of C. sinensis and O. viverrini. This spatial delineation offers valuable insights for integrated surveillance and control strategies, particularly in regions with sympatric transmission. The results underscore the need for tailored interventions, considering regional epidemiological variations. Future collaborations integrating eco-epidemiology, molecular epidemiology, and parasitology are essential to further elucidate the complex interplay of liver fluke distributions in Asia.

摘要

背景

华支睾吸虫和肝片形吸虫分别引起的华支睾吸虫病和肝片形吸虫病,是亚洲重要的被忽视热带病(NTD)。这些病原体在重叠地区共存,使有效的疾病控制策略变得复杂。本研究旨在阐明东南亚地区这些疾病的分布和相互作用。

方法

我们系统地收集了东南亚国家的人类华支睾吸虫病(n=1809)和肝片形吸虫病(n=731)的发病记录。我们利用包含环境和气候数据的物种分布模型,结合机器学习算法和增强回归树,预测并区分了每种吸虫的流行地区。我们还利用地理空间分析等机器学习技术来划定这些吸虫的边界。

结果

我们的分析表明,华支睾吸虫和肝片形吸虫在东南亚的流行范围主要分布在中国、越南、泰国、老挝和柬埔寨的部分地区。在 2000 年至 2018 年期间,我们在 84 个不同的地点发现了华支睾吸虫感染,主要在中国南部(广西壮族自治区)和越南北部。相比之下,肝片形吸虫的分布更为广泛,在泰国、老挝、柬埔寨和越南的 721 个地点都有记录。我们还对关键的环境决定因素进行了定量分析,结果表明,华支睾吸虫病流行地区的年平均温度在 14 到 20°C 之间,肝片形吸虫病流行地区的年平均温度在 24 到 30°C 之间(P<0.05)。机器学习模型有效地绘制了一个明显的分界线,表明这两种肝吸虫的流行地区之间有明显的分离,AUC 值在 0.9 到 1 之间。在越南的研究还划定了华支睾吸虫和肝片形吸虫共存的地理边界,揭示了这两种肝吸虫的特有流行区和重叠的过渡区。

结论

我们的研究结果强调了特定气候和环境因素在影响华支睾吸虫和肝片形吸虫地理分布方面的关键作用。这种空间划分提供了对综合监测和控制策略的有价值的见解,特别是在具有共生传播的地区。研究结果强调了需要根据区域流行病学差异采取有针对性的干预措施。未来需要整合生态流行病学、分子流行病学和寄生虫学的合作研究,以进一步阐明亚洲肝吸虫分布的复杂相互作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/18e5/10935802/b808c98a3ca0/40249_2024_1191_Fig1_HTML.jpg

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