Landscape Pattern Analysis and Bayesian Modeling for Predicting Oncomelania hupensis Distribution in Eryuan County, People’s Republic of China

Kun Yang Jiangsu Institute of Parasitic Diseases, Wuxi, People’s Republic of China; National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People’s Republic of China; Department of Public Health and Epidemiology, Swiss Tropical Institute, Basel, Switzerland; Eryuan Schistosomiasis Control Station, Eryuan, People’s Republic of China

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Xiao-Nong Zhou Jiangsu Institute of Parasitic Diseases, Wuxi, People’s Republic of China; National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People’s Republic of China; Department of Public Health and Epidemiology, Swiss Tropical Institute, Basel, Switzerland; Eryuan Schistosomiasis Control Station, Eryuan, People’s Republic of China

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Xiao-Hua Wu Jiangsu Institute of Parasitic Diseases, Wuxi, People’s Republic of China; National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People’s Republic of China; Department of Public Health and Epidemiology, Swiss Tropical Institute, Basel, Switzerland; Eryuan Schistosomiasis Control Station, Eryuan, People’s Republic of China

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Peter Steinmann Jiangsu Institute of Parasitic Diseases, Wuxi, People’s Republic of China; National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People’s Republic of China; Department of Public Health and Epidemiology, Swiss Tropical Institute, Basel, Switzerland; Eryuan Schistosomiasis Control Station, Eryuan, People’s Republic of China

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Xian-Hong Wang Jiangsu Institute of Parasitic Diseases, Wuxi, People’s Republic of China; National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People’s Republic of China; Department of Public Health and Epidemiology, Swiss Tropical Institute, Basel, Switzerland; Eryuan Schistosomiasis Control Station, Eryuan, People’s Republic of China

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Guo-Jing Yang Jiangsu Institute of Parasitic Diseases, Wuxi, People’s Republic of China; National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People’s Republic of China; Department of Public Health and Epidemiology, Swiss Tropical Institute, Basel, Switzerland; Eryuan Schistosomiasis Control Station, Eryuan, People’s Republic of China

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Jürg Utzinger Jiangsu Institute of Parasitic Diseases, Wuxi, People’s Republic of China; National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People’s Republic of China; Department of Public Health and Epidemiology, Swiss Tropical Institute, Basel, Switzerland; Eryuan Schistosomiasis Control Station, Eryuan, People’s Republic of China

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Hong-Jun Li Jiangsu Institute of Parasitic Diseases, Wuxi, People’s Republic of China; National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People’s Republic of China; Department of Public Health and Epidemiology, Swiss Tropical Institute, Basel, Switzerland; Eryuan Schistosomiasis Control Station, Eryuan, People’s Republic of China

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Detailed knowledge of how local landscape patterns influence the distribution of Oncomelania hupensis, the intermediate host snail of Schistosoma japonicum, might facilitate more effective schistosomiasis control. We selected 12 villages in a mountainous area of Eryuan County, Yunnan Province, People’s Republic of China, and developed Bayesian geostatistical models to explore heterogeneities of landscape composition in relation to distribution of O. hupensis. The best-fitting spatio-temporal model indicated that the snail density was significantly correlated with environmental factors. Specifically, snail density was positively correlated with wetness and inversely correlated with the normalized difference vegetation index and mollusciciding, and snail density decreased as landscape patterns became more uniform. However, the distribution of infected snails was not significantly correlated with any of the investigated environmental factors and landscape metrics. Our enhanced understanding of O. hupensis ecology is important for spatial targeting of schistosomiasis control interventions.

Author Notes

Reprint requests: Xiao-Nong Zhou, National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, 207 Rui Jin Er Road, Shanghai 200025, People’s Republic of China, E-mail: ipdzhouxn@sh163.net.
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