Schistosomiasis, a prevalent public health issue specifically in sub-Saharan Africa, is primarily attributed to Schistosoma haematobium and Schistosoma mansoni, often occurring concurrently. These schistosome species share similarities in life cycles and transmission, manifesting comparable infection patterns and susceptibility to temperature variations. This study investigates the influence of temperature control not only on the transmission of individual species but also on their mutual interactions and co-infection dynamics using a mathematical model. Sub-models and co-dynamic properties, including reproduction numbers, equilibrium states, and stability conditions, are derived. Sensitivity analysis is performed to clarify the impact of parameter variations on model stability. Results suggest that temperature variation increases the spread of S. haematobium, which enhances susceptibility to S. mansoni co-infection, possibly by altering the immune response. At moderate temperatures (20 degrees C and 25 degrees C), infection levels in both single and co-infected individuals are higher, while recovery rates increase with temperature, peaking at 25 degrees C and 35 degrees C as infections significantly decrease. Biomphalaria snails exhibit greater population growth and susceptibility to infection than Bulinus snails, particularly below 25 degrees C. Above this temperature, Biomphalaria population decreases while Bulinus species are more likely to experience faster mortality. These temperature-related variations differently impact mortality rates of intermediate snails and snail-to-human transmissibility rates for schistosome species, holding significant health implications. Targeting snails during seasons below 25 degrees C, when susceptibility is higher, and intensifying human treatment interventions around 25 degrees C-35 degrees C, where recovery rates peak, may yield optimal results, particularly during seasons with intermediate temperatures around 25 degrees C for both snails and humans. The results underscore the importance of integrating temperature into models for predicting and managing schistosomiasis dynamics for both genera. Therefore, this model is applicable not only to sub-Saharan Africa, but also to other regions where the described temperature ranges match with the local climate.