Epidemiology and risk factors of Clonorchis sinensis infection in the mountainous areas of Longsheng County, Guangxi: insights from automated machine learning.

IF 2 3区 医学 Q2 PARASITOLOGY
Xiaowen Li, Yu Chen, Guoyang Huang, Xuerong Sun, Gang Mo, Xiaohong Peng
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Abstract

Clonorchis sinensis (C. sinensis) is mainly prevalent in Northeast and South China, with Guangxi being the most severely affected region. This study aimed to evaluate the prevalence and identify the risk factors of C. sinensis infection in Longsheng County, a mountainous area in northern Guangxi. In 2023, a comprehensive study was conducted in Longsheng County, utilizing longstanding inhabitants as study participants. Questionnaires were employed to gather data on fish consumption, awareness of C. sinensis, and residential coordinates, while fecal examinations were utilized to identify C. sinensis infection. Important risk factors for the C. sinensis infection were identified through the development of individual infection risk models using automated machine learning techniques. A total of 740 fecal samples were collected, revealing an overall C. sinensis infection rate of 69.59%. The gradient boosting machine (GBM) was the most accurate predictor with an area under the precision-recall Curve (AUPRC) of 0.997. The model identified years of raw fresh fish consumption, frequency of raw fresh fish consumption, elevation, and water distance as the top four predictors of C. sinensis infection risk. In conclusion, our study has revealed a high infection rate of C. sinensis in the mountainous areas of Longsheng County, with adults, men, and farmers particularly susceptible to both high incidence and infection severity. We developed a high-performance predictive model for individual C. sinensis infection within the county, identifying the key risk factors for local infections. These findings offer valuable guidance for the control and prevention of clonorchiasis.

广西龙胜县山区华支睾吸虫感染流行病学及危险因素分析:基于自动机器学习的分析
华支睾吸虫(C. sinensis)主要分布在东北和华南地区,广西是感染最严重的地区。本研究旨在了解广西北部山区龙胜县中华按蚊的流行情况,并探讨其感染的危险因素。2023年,在隆盛县进行了一项综合研究,研究对象是长期居住的居民。通过问卷调查收集鱼类消费、中华梭菌认知和居住坐标等数据,通过粪便检查确定中华梭菌感染情况。利用自动机器学习技术建立个体感染风险模型,确定了中华按蚊感染的重要危险因素。共收集粪便740份,中华按蚊感染率为69.59%。梯度增强机(GBM)预测精度最高,精确召回曲线下面积(AUPRC)为0.997。该模型确定了食用生鲜鱼的年份、食用生鲜鱼的频率、海拔高度和水距离是中华梭菌感染风险的前四个预测因素。综上所述,龙胜县山区中华按蚊感染率较高,成人、男性和农民易感,发病率高,感染严重程度高。我们建立了一个高性能的县内中华按蚊个体感染预测模型,确定了当地感染的关键危险因素。这些发现对支睾吸虫病的控制和预防具有指导意义。
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来源期刊
Parasitology Research
Parasitology Research 医学-寄生虫学
CiteScore
4.10
自引率
5.00%
发文量
346
审稿时长
6 months
期刊介绍: The journal Parasitology Research covers the latest developments in parasitology across a variety of disciplines, including biology, medicine and veterinary medicine. Among many topics discussed are chemotherapy and control of parasitic disease, and the relationship of host and parasite. Other coverage includes: Protozoology, Helminthology, Entomology; Morphology (incl. Pathomorphology, Ultrastructure); Biochemistry, Physiology including Pathophysiology; Parasite-Host-Relationships including Immunology and Host Specificity; life history, ecology and epidemiology; and Diagnosis, Chemotherapy and Control of Parasitic Diseases.
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