Cryptosporidium Infection Risk: Results of New Dose‐Response Modeling

Abstract

Cryptosporidium human dose-response data from seven species/isolates are used to investigate six models of varying complexity that estimate infection probability as a function of dose. Previous models attempt to explicitly account for virulence differences among C. parvum isolates, using three or six species/isolates. Four (two new) models assume species/isolate differences are insignificant and three of these (all but exponential) allow for variable human susceptibility. These three human-focused models (fractional Poisson, exponential with immunity and beta-Poisson) are relatively simple yet fit the data significantly better than the more complex isolate-focused models. Among these three, the one-parameter fractional Poisson model is the simplest but assumes that all Cryptosporidium oocysts used in the studies were capable of initiating infection. The exponential with immunity model does not require such an assumption and includes the fractional Poisson as a special case. The fractional Poisson model is an upper bound of the exponential with immunity model and applies when all oocysts are capable of initiating infection. The beta Poisson model does not allow an immune human subpopulation; thus infection probability approaches 100% as dose becomes huge. All three of these models predict significantly (>10x) greater risk at the low doses that consumers might receive if exposed through drinking water or other environmental exposure (e.g., 72% vs. 4% infection probability for a one oocyst dose) than previously predicted. This new insight into Cryptosporidium risk suggests additional inactivation and removal via treatment may be needed to meet any specified risk target, such as a suggested 10 annual risk of Cryptosporidium infection.

Screening of protozoan and microsporidian parasites in feces of great cormorant (Phalacrocorax carbo)

“…These microorganisms are resistant to various environmental conditions, can lead to serious, acute gastrointestinal infections in human, and are usually characterized by the low infectious dose (Szumowski and Troemel 2015; Messner and Berger 2016). The presence of Cryptosporidium oocysts and Giardia cysts in source waters have already caused numerous documented outbreaks related in both drinking and recreational waters (Karanis et al 2007).…”

Developing a characterization factor framework for microbial contamination

“…This factor was determined as: A dose-response assessment determines the relation between the concentration of oocyst that enter the host' body (dose), and possible infection (risk). This study used six doseresponse models for pathogen infection developed by Messner [10]. The order of models represents an increase of complexity, which are fractional Poisson model, an exponential model, exponential with immunity model, beta-Poisson model, hierarchical beta-Poisson model, and hierarchical logistic model.…”

“…A higher discharge may decrease oocyst concentrations due to dilution [15] or increase the microorganism concentration due to resuspension from sediments and increased runoff [8]. Figure 3 below shows the effect factor value from six different dose-response models by Messner [10]. The effect factor value ranges from 0.0022 to 0736 cases/oocyst.…”

Cryptosporidium and Cryptosporidiosis: The Perspective from the Gulf Countries

“…Cryptosporidium oocysts transmission can occur following direct or indirect contact with an infected host usually via the faecal-oral route. Person-to-person contact, zoonosis, and the consumption of contaminated food or water are well known mechanisms for faecal-oral transmission [2,3], with a significant risk of infection from the ingestion of a single oocyst [4]. When the oocysts enter the gastrointestinal tract, the invasive Cryptosporidium causes damage to the small intestinal epithelium.…”