Prediction on the spatial distribution of the seropositive rate of schistosomiasis in Hunan Province, China: a machine learning model integrated with the Kriging method

• Published in: Parasitology research (1987) Vol. 123; no. 9; p. 316
• Main Authors: Xu, Ning, Cai, Yu, Tong, Yixin, Tang, Ling, Zhou, Yu, Gong, Yanfeng, Huang, Junhui, Wang, Jiamin, Chen, Yue, Jiang, Qingwu, Zheng, Mao, Zhou, Yibiao
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2024; Springer Nature B.V
• Subjects: Animals; Biomedical and Life Sciences; Biomedicine; China; China - epidemiology; gross domestic product; Humans; Immunology; kriging; lakes; Learning algorithms; Machine Learning; Medical Microbiology; Microbiology; Models, Statistical; prediction; Public health; rivers; Schistosomiasis; Schistosomiasis - epidemiology; Schistosomiasis - prevention & control; Seroepidemiologic Studies; seroprevalence; Spatial Analysis; Spatial distribution; surface temperature; wind speed; China; Hunan China; Schistosomiasis; Seropositive Rate; Machine Learning; Geostatistical method; Spatial Distribution

Schistosomiasis remains a formidable challenge to global public health. This study aims to predict the spatial distribution of schistosomiasis seropositive rates in Hunan Province, pinpointing high-risk transmission areas and advocating for tailored control measures in low-endemic regions. Six machi...