Prediction of on comelania hupensis (vector of schistosomiasis) distribution based on remote sensing data and fuzzy information theory

Schistosomiasis is a parasitic disease that menaces human health. In terms of impact, this disease is second only to malaria as the most devastating parasitic disease. Oncomelania hupensis (snail) is the unique intermediate host of schistosoma, so monitoring and controlling of the number of snail is key to reduce the risk of schistosomiasis transmission. Remote sensing technology can real-timely access the large-scale environmental factors related to snail breeding and reproduction, then can also provide the efficient information to determine the location, area, and spread tendency of snail. But the complex relationship between snail and various environmental factors limit its development. To solve above problem, in this study, the fuzzy information theory was employed to analyze the relationship between snail density and environmental factors. A model for predicting snail distribution and density was developed and validated with field data of Dongting Lake. The validation results demonstrated the success of the developed model in predicting the distribution of Oncomelania hupensis.