Additional file 1: Table S1. of Longitudinal survey on the distribution of Biomphalaria sudanica and B. choanomophala in Mwanza region, on the shores of Lake Victoria, Tanzania: implications for schistosomiasis transmission and control

Negative Binomial GLMMs for B. sudanica abundance showing coefficient effects estimates and confidence intervals (CI) for the following explanatory variables: monthly temperature, water levels at sites, water properties (water temperature & pH), and accumulative precipitation. Table S2. Zero-inflated negative binomial GLMM for B. choanomphala abundance showing coefficient effects estimates and confidence intervals (CI) for the following explanatory variables: monthly temperature, accumulative precipitation and districts. Table S3. Hurdle models: truncated quasi-Poisson binomial for B. choanomphala abundance and binomial for B. choanomphala presence/absence with coefficient effects estimates and confidence intervals (CI) for the following explanatory variables: monthly temperature, accumulative precipitation and longitude and latitude coordinates. Table S4. Zero-inflated negative binomial GLMM for shedding Biomphalaria abundance and binomial model for presence/absence of shedding Biomphalaria with coefficient effects estimates and confidence intervals (CI) for the following explanatory variables: B. sudanica abundance, B. choanomphala abundance, monthly temperature, accumulative precipitation, presence/absence of human water-based activities (bathing, washing, water collecting), presence/absence of farming activities, presence/absence of other molluscs (other snails and bivalves), year of collection and an interaction term between average temperature and accumulative precipitation. In all tables the symbol * indicates a statistically significant effect of the coefficient estimate (P