Matrix effects, nonuniform reduction and dispersion in risk assessment for Escherichia coli O157

Open Access
Publisher Website
Google Scholar
Abstract
Aims: To assess the importance of the variation (or spatial heterogeneity) in the doses of Escherichia coli O157 ingested by individuals when estimating the group risk. Methods and Results: Exposure scenarios, which differed in how the same total number of E. coli O157 cells were distributed across a group of persons were simulated and the risks of illness in the population estimated using available dose–response data. Differences in the degree of spatial heterogeneity within routes such as direct contact with sheep faeces, consumption of hamburgers and drinking water could affect the magnitude of the predicted risk by over 1000-fold and contribute to an apparent matrix effect. The effect of barriers, such as cooking, on the spatial heterogeneity of E. coli O157 cells remaining in undercooked hamburgers affects the magnitude of the risk by eightfold. Furthermore, a 100-fold reduction in E. coli O157 concentrations by cooking may reduce the risk of illness from consumption of the burgers by only 12-fold (and not the 100-fold perhaps expected). Conclusions: The development of microbiological risk assessment (MRA) models for E. coli O157 requires information on the degree of dispersion of faeces within routes such as the environment, food and water, so that the proportion of persons actually exposed to faeces, and hence pathogen, can be quantified. The effect of dispersion is greater for pathogens for which there is greater variation in susceptibility within the population. Significance and Impact of the Study: In terms of public health protection, minimizing the dispersion of cattle/sheep faeces reduces the risks to humans by confining exposure to fewer individuals. For MRA, estimating the reduction in risk by a treatment process, e.g. cooking, is complicated by spatial heterogeneity. Regional differences in dispersion (e.g. because of rainfall) may contribute to regional differences in the observed attack rate.