Diarrhoeal disease is very common around the world. Knowing more about the global burden of diarrhoeal disease and about the geographical distribution of pathogen pollution is important for decision making and water and sanitation planning. The objective of this thesis is to increase knowledge on the sources, fate and transport of Cryptosporidium in rivers worldwide using spatially explicit modelling. I present the Global Waterborne Pathogen model for Cryptosporidium (GloWPa-Crypto), the first global model of waterborne pathogen emissions to and concentrations in rivers. The model is used to provide information on pathogen concentrations in data-sparse regions, identify hotspot regions, identify the relative contribution of different sources, and in scenario analysis to study the impacts of global change or management strategies. Furthermore, the model can be applied in the analysis of risk, burden of disease and health-based treatment targets, and make a valuable contribution in meeting the Sustainable Development Goals.