A model for the prediction of Oncomelania hupensis in the lake and marshland regions, China.

A model has been developed for predicting the density of Oncomelania hupensis, the intermediate host snail of Schistosoma japonicum. The model takes into account different environmental factors, including elevation, air and soil temperature, type of vegetation, mean height of preponderant vegetation and soil humidity. Deviance and Akaike information criteria were used to determine the best model fits. Model diagnostics and internal and external validations of model efficiency were also performed. From the final prediction model, two important results emerge. First, air temperature should be used with care to study the distribution of O. hupensis and to predict its potential survival because the impact is indirect, and it is weaker and more unstable than soil temperature. Second, the more important environmental factor for O. hupensis prediction at the microscale is soil humidity, but the more important macroscale environmental factor is soil temperature. This finding might help in selecting different environmental features for studying O. hupensis at different spatial scales. Our model is promising for predicting the density of O. hupensis, and hence can provide more objective information about snail dispersal, which might eventually replace the tedious and imprecise field work for annual surveillance of O. hupensis.