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

• Published in: Infectious diseases of poverty Vol. 13; no. 1; pp. 24 - 13
• Main Authors: Zheng, Jin-Xin, Zhu, Hui-Hui, Xia, Shang, Qian, Men‐Bao, Nguyen, Hung Manh, Sripa, Banchob, Sayasone, Somphou, Khieu, Virak, Bergquist, Robert, Zhou, Xiao-Nong
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 12.03.2024; BioMed Central; BMC
• Subjects: Algorithms; Analysis; Boundaries; Climatic data; Clonorchiasis; Clonorchis sinensis; Coexistence; Data mining; Disease; Disease control; Eggs; Endemic species; Environmental conditions; Environmental factors; Epidemiology; Geographical distribution; Geospatial data; Health aspects; Infections; Literature reviews; Liver; Liver fluke; Machine learning; Medical research; Medicine, Experimental; Opisthorchiasis; Opisthorchis viverrine; Parasites; Provinces; Regions; Risk factors; Southeast Asia; Subject heading schemes; Southeast Asia; Vietnam; Thailand; Laos; China; Cambodia; Asia; Mekong River; Opisthorchis viverrine; Southeast Asia; Opisthorchiasis; Ecological study; Liver fluke; Machine learning; Clonorchiasis; Clonorchis sinensis
• DOI: 10.1186/s40249-024-01191-7
• ISSN: 2049-9957; 2095-5162

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. 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. 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. 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.