Landscape pattern analysis and Bayesian modeling for predicting Oncomelania hupensis distribution in Eryuan County, People's Republic of China

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