“…[7] The model parameters reflect the characteristics of Cryptosporidium parvum oocysts, a waterborne pathogen behind several notable outbreaks of waterborne disease and a subject of many studies [see, e.g., Atherholt et al, 1998;Atwill et al, 2006;Dai and Boll, 2006;Dorner et al, 2006;Searcy et al, 2006]. Cryptosporidium, like many other microbes and chemicals, is heterogeneously distributed in the environment, its transport is driven by random events, it has a low infectious dose and is expensive to monitor [Curriero et al, 2001;Gale, 1998;Nnane et al, 2012;Richardson et al, 1991;Yeghiazarian et al, 2009]. For these reasons, the decision-making process aiming to reduce human exposure to this, and many other pathogens and contaminants, must ultimately rest with mathematical models capable of capturing its occurrence and transport.…”