In this study, we investigate the extent to which the incidence of Escherichia coli O157:H7 can be predicted in human faeces, from human intake and infection via water contaminated by livestock and carrying this zoonotic pathogen in North-East (NE) and South-West (SW) regions of Scotland. In SW Scotland, there is a risk of coastal recreational waters failing EU standards for faecal indicator organisms, and this is assumed to be the main potential waterborne route of infection. In NE Scotland, the main waterborne route is assumed to be the many private drinking water supplies; these are mainly derived from shallow groundwater and surveys show that there is potential for significant levels of microbial contamination from livestock. The risk to human health from these sources has been assessed using a combination of process models, epidemiological risk-assessment methods and survey data. A key assumption in the calculations is the amount of mixing of pathogenic and non-pathogenic E. coli between animal faecal sources and contaminated water intake by humans. Using the probability distributions of the E. coli O157 content of individual faecal pat material (which would imply no mixing between source and human intake), based on three recent surveys of animal faeces in Scotland, led to predicted annual risks of infection slightly higher than observed human infection incidence. Using the geometric mean to represent partial mixing (which theoretically may over- or underestimate incidence with a concave dose–response curve) gave infection rates similar to those observed for two of the three faecal surveys. Using the arithmetic mean led to over-prediction of risk. This is to be expected if the true dose–response curve is (such as the Beta-Poisson curve used here) concave. Other factors that may lead to over-prediction of incidence are discussed, including under-reporting, loss of infectivity as a result of environmental exposure, immunity and the appropriateness of the Beta-Poisson curve. It is concluded that better epidemiological data for calibration of the dose–response curve, better knowledge of the degree of mixing and understanding of immunity are key requirements for progress in process model-based predictions of infection rate. The paper also explores the potential of improved farm and catchment scale management to deliver cost-effective mitigation of pollution of bathing and drinking water by livestock zoonoses.