Muenjak Jarawadee, Thongrod Jutarat, Choodamdee Chanakan, Pongpanitanont Pongphan, Yingklang Manachai, Thanchomnang Tongjit, Laymanivong Sakhone, Janwan Penchom
Department of Medical Technology, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, 80160, Thailand.
Health Sciences (International Program), College of Graduate Studies, Walailak University, Nakhon Si Thammarat, 80160, Thailand.
Sci Rep. 2025 Aug 4;15(1):28432. doi: 10.1038/s41598-025-14221-7.
Soil-transmitted helminth (STH) infections remain a significant public health concern in rural areas, often leading to nutritional and physical impairment, particularly in children. This study aimed to assess the prevalence and associated factors of STH infections among schoolchildren in Thasala District, Nakhon Si Thammarat Province, Thailand, and to develop a predictive model for identifying high-risk areas using satellite imagery data. A cross-sectional study was conducted with 319 primary schoolchildren from six sub-districts in Thasala District. Stool samples were analyzed for STH infections using the formalin ethyl acetate concentration technique (FECT) and agar plate culture (APC), while behavioral data were collected through questionnaires to identify key risk factors. We developed an innovative predictive model by integrating convolutional neural networks (CNNs) for land-use classification of satellite imagery with artificial neural networks (ANNs) following dimensionality reduction through principal component analysis (PCA). The STH infections were detected in 31 samples (9.72%), with higher prevalence in males (11.38%) than females (8.67%). Mono-infections predominated, with Trichuris trichiura (5.02%) and hookworm (3.49%) being the most frequent. Mixed infections accounted for 1.25%, primarily co-infections of hookworm with T. trichiura (0.94%) or Strongyloides stercoralis (0.31%). Not cutting nails was identified as a significant behavioral factor associated with STH infections (p = 0.047), while other behavioral factors showed no statistical significance. From the satellite imagery analysis, specific environmental features, particularly higher proportions of agricultural land and closer proximity to water bodies, were positively associated with elevated STH prevalence. The modelling approach generated spatial risk maps for STH infections, providing a cost-effective tool for identifying high-risk transmission zones. These findings highlight that STH infections persist among rural Thai schoolchildren, with poor hygiene practices as a contributing factor. Strengthening hygiene education, improving sanitation, and implementing targeted environmental interventions are essential for effective control.
土壤传播的蠕虫(STH)感染仍是农村地区一个重大的公共卫生问题,常常导致营养和身体损害,尤其是在儿童中。本研究旨在评估泰国那空是贪玛叻府塔沙拉区学童中STH感染的患病率及相关因素,并利用卫星图像数据建立一个识别高危地区的预测模型。对塔沙拉区六个分区的319名小学生进行了一项横断面研究。采用福尔马林乙酸乙酯浓缩技术(FECT)和琼脂平板培养(APC)对粪便样本进行STH感染分析,同时通过问卷调查收集行为数据以确定关键风险因素。我们通过将用于卫星图像土地利用分类的卷积神经网络(CNN)与经过主成分分析(PCA)降维后的人工神经网络(ANN)相结合,开发了一种创新的预测模型。在31个样本(9.72%)中检测到STH感染,男性患病率(11.38%)高于女性(8.67%)。单一感染占主导,其中鞭虫(5.02%)和钩虫(3.49%)最为常见。混合感染占1.25%,主要是钩虫与鞭虫的合并感染(0.94%)或粪类圆线虫感染(0.31%)。不剪指甲被确定为与STH感染相关的一个重要行为因素(p = 0.047),而其他行为因素无统计学意义。从卫星图像分析来看,特定的环境特征,特别是农业用地比例较高和更靠近水体,与STH患病率升高呈正相关。该建模方法生成了STH感染的空间风险地图,为识别高危传播区域提供了一种经济有效的工具。这些发现突出表明,泰国农村学童中STH感染依然存在,不良卫生习惯是一个促成因素。加强卫生教育、改善环境卫生并实施有针对性的环境干预措施对于有效防控至关重要。