Populations of beef cattle represent a potential non-point source of environmental contamination for Cryptosporidium parvum if on-farm management practices fail to minimize transport from bovine manure to adjacent water sources. Characterizing this risk of contamination requires several parameters to be estimated, the most important being a valid and precise estimate of the oocyst loading rate per animal unit. The oocyst loading rate is defined in this study as the total number of oocysts excreted by a cohort of adult beef cows during a 24[emsp4 ]h period. We propose a methodology for estimating this parameter for low prevalent populations whereby the majority of individuals are test negative. Under specific degrees of confidence and at the population scale, this methodology generates estimates for maximal oocyst loading based on the sensitivity of the diagnostic test and the point prevalence and intensity of fecal shedding from a cross-sectional survey of the target population.

Escherichia coli O157:H7 is an emerging food and waterborne pathogen in the U.S. and internationally. The objective of this work was to develop a dose-response model for illness by this organism that bounds the uncertainty in the dose-response relationship. No human clinical trial data are available for E. coli O157:H7, but such data are available for two surrogate pathogens: enteropathogenic E. coli (EPEC) and Shigella dysenteriae. E. coli O157:H7 outbreak data provide an initial estimate of the most likely value of the dose-response relationship within the bounds of an envelope defined by beta-Poisson dose-response models fit to the EPEC and S. dysenteriae data. The most likely value of the median effective dose for E. coli O157:H7 is estimated to be approximately 190[emsp4 ]000 colony forming units (cfu). At a dose level of 100[emsp4 ]cfu, the median response predicted by the model is six percent.

Monte-Carlo simulations were performed in order to quantify the microbiological risk arising from the presence of Giardia and Cryptosporidium in drinking water. A two-year survey of 45 utilities located on a portion of the St. Lawrence River (Quebec, Canada) allowed us to collect the information required for this assessment: parasite occurrence data, treatment performances and daily unboiled water consumption. For a conventional treatment, the mean annual risk of infection with Cryptosporidium was found to be approximately eight times higher than with Giardia. The Monte-Carlo simulations confirm that the clarification process plays an important role in the reduction of the health risk associated with protozoan parasites. In fact, in the case of Cryptosporidium, the impact of chemical disinfectants (O3 or Cl2) appears to be minimal in the cold water treatment conditions prevailing in Quebec. According to the Monte-Carlo simulations, 45% (for conventional treatment+O3) and 51% (for conventional treatment) of individuals are exposed to a risk of infection with Cryptosporidium higher than the proposed USEPA guideline (1 infection per 10[emsp4 ]000 individuals per year).

Data from several studies were appended to aerobic and anaerobic data sets that had been previously used to develop response surface models describing the growth kinetics of Listeria monocytogenes (Buchanan and Phillips, 1990). The expanded data sets included 709 aerobic and 358 anaerobic growth curves fitted with the Gompertz equation, and representing 189 and 150 unique combinations of four variables (temperature, pH, NaCl, NaNO2), respectively. Response surface models were developed for (1) the Gompertz B and M terms and (2) lag phase durations (LPD) and generation times (GT). In addition to modeling NaCl as a variable, a second set of response surface models was developed by substituting calculated water activity as a variable. A number of data transformations were evaluated in an attempt to better utilize no-growth data. Full quadratic models of the natural logarithm transformation of the data (no-growth data excluded) predicted values that fit the observed data well. The assignment of GT=50[emsp4 ]h and LPD=600[emsp4 ]h (the approximate maximum duration of experiments) for the variable combinations that did not support growth proved to be the most effective means of making use of the no-growth data. However, this approach did not offer any clear advantage over quadratic models where the no-growth data were excluded. Error matrices were developed for the LPD and GT models to provide 95 % confidence intervals. The agreement between observed and predicted growth kinetics was excellent considering the number and ranges of the variables encompassed in the models. The models provide reasonable predictions of the growth of L. monocytogenes in foods. The full quadratic models of LPD and GT without inclusion of the no-growth data were selected for inclusion in the USDA Pathogen Modeling Program, release 5.1.

Tail moments in the single cell gel electrophoresis (comet) assay usually do not follow a normal distribution, making the statistical analysis complicated. Researchers have used a wide variety of statistical techniques in an attempt to overcome this problem. In many cases, the tail moments follow a bimodal distribution that can be modeled with a mixture of gamma distributions. This bimodality may be due to cells being in two different stages of the cell cycle at the time of treatment. Maximum likelihood, modified to accommodate censored data, can be used to estimate the five parameters of the gamma mixture distribution for each slide. A weighted analysis of variance on the parameter estimates for the gamma mixtures can be performed to determine differences in DNA damage between treatments. These methods were applied to an experiment on the effect of thymidine kinase in DNA damage and repair. Analysis based on the mixture of gamma distributions was found to be more statistically valid, more powerful, and more informative than analysis based on log-transformed tail moments.

The serious limitation of the available human data contributes to the need for making simplifying assumptions for dose-response modeling which has led to frequent use of a single function, the beta-Poisson function, as a default dose-response model form. This function is a concave, low-dose linear function. Sub-linear or convex curves may be more appropriate for some host-pathogen interactions due to the series of highly regulated innate and acquired defense systems of the healthy human body that protect against most microbial challenges. A systematic investigation of the steps of non-typhoid salmonellosis in humans leads to biological motivations for sub-linear, or non-concave, dose-response curves in microbial risk assessment. Three phenomena were identified that might contribute to sub-linear, or non-concave, dose-response curves: (1) clumping of bacterial cells in microcolonies in a food matrix; (2) quorum sensing, or density-dependency in expression of virulence genes or other metabolic actions; and (3) need, at least in some circumstances, for multiple lesions for progression to symptomatic illness. This investigation suggests that microbial risk assessors should routinely employ a variety of model forms in addition to the commonly used beta-Poisson model to depict more fully the uncertainty of the “true” dose-response model.

A computer simulation model which describes the spatial and temporal variation in the extent of listerial contamination within a damaged silage bale is presented. The silage bale is assumed to be split into a number of distinct sites and these sites are represented by a two dimensional lattice structure. Each site is classified in relation to its listerial composition. This classification results in three states which are dormant, active and unpopulated. Sites change state as a result of the movement of oxygen through the bale. This movement is initiated when a hole is punched in the plastic covering of the bale. The model is stochastic in nature and at any time following damage, the proportion of the bale which is contaminated is calculated. Furthermore, the spatial distribution of contaminated sites is predicted. The models are a first attempt at introducing structure into the selection process for feeding silage. We highlight areas of future research which will be invaluable for validation and practical use of the model.

An assessment was made to determine the potential loading of enteric pathogenic protozoa and viruses into drinking water supply reservoirs by body contact recreation. These and other organisms of fecal origin are shed from the body during bathing. A literature review was conducted on the concentration of selected enteric viruses and protozoa during infection, the incidence of these infections, and duration of excretion. In addition, from existing literature, the amount of fecal material released during bathing was estimated from the shedding of fecal coliforms by bathers. The mean amount of fecal material shed per bather was estimated at 0.14[emsp4 ]gram. The concentration of protozoan parasites (Giardia or Cryptosporidium) in feces of infected persons can range from 105 to 107 per gram and enteric viruses (enteroviruses, adenoviruses, rotavirus) from 105 to 1012 per gram. From this information, the concentration of enteric pathogens, shed into the water, could be calculated for a group of bathers. This information can be used to model the impact of body contact recreation on water quality in reservoirs used for drinking water supplies. Such information is useful in assessing the required treatment of the water to meet water quality regulations.

Cryptosporidium parvum is a common contaminant in surface waters and presents significant problems for the water industry, public health and agriculture. Consequently, ascertaining the contaminating source of waterborne oocysts is of paramount importance. Based on currently available information, isolates of C. parvum can be differentiated into at least two genotypes using polymorphic genetic markers: genotype 1, to date isolated almost exclusively from humans, and genotype 2 isolates from humans and many other animals. Differentiation into these two genotypes has been based on either restriction fragment length polymorphisms or sequencing of PCR amplified gene fragments. The objective of this study was to evaluate the reproducibility of genotyping methods using a single isolate of C. parvum. A 620 bp fragment of the C. parvum β-tubulin gene, generated by PCR from multiple aliquots of a single preparation of oocysts of the Iowa isolate, was sequenced. Significant sequence heterogeneity was detected within this single isolate; there was more sequence variation between clones originating from the Iowa isolate (up to 0.9 %) than between individual clones originating from different isolates of C. parvum. Over 6 % of the β-tubulin gene sequence positions (38 out of 620 bp) were variable when comparing multiple clones from the one isolate. The results indicated that while the various procedures used for genotyping isolates may introduce some sequence errors, the Iowa isolate used for this investigation appeared to be composed of multiple sub-genotypes. While none of the sequence variations resulted in clones of the Iowa isolate (genotype 2) being mis-identified as genotype 1, the results have important implications if minor sequence variations are to be used for subtyping isolates and drawing conclusions regarding the origin of, or relationships between, C. parvum oocysts in water and the community.

Experiments with batch suspensions, recirculating columns and flow-through columns have been carried out involving a sandy soil and five bacteriophages: MS2, PRD1, φX174, Qβ and PM2. In batch and recirculating column experiments, attachment and detachment rate coefficients were determined by fitting a two-parameter (attachment and detachment) model. In general, attachment and detachment rate coefficients were not found to be significantly different between the two kinds of experiments. There was one exception, however: MS2 appeared to detach faster in the presence of strong advective flow. In the case of flow-through column experiments, it is shown that a two-site model, with adsorption to equilibrium and kinetic sites, fits the breakthrough curves of all the phages, except PM2, satisfactorily. A one-site kinetic model was found to be appropriate for phage PM2. A small proportion of bacteriophages MS2, PRD1, and Qβ adsorbed to equilibrium sites, whereas a large proportion of φX174 adsorbed to equilibrium sites. Such a distinction between adsorption to equilibrium and kinetic sites cannot be made in the case of batch or recirculating column experiments. Kinetic attachment rate coefficients were found to be significantly higher for the bacteriophages with presumably stronger negative charge. This may be ascribed to the presence of multivalent cations. Under these conditions, bacteriophage φX174 appears to behave more conservatively than more negatively charged viruses, and may then be a better choice as a relatively conservative tracer for virus transport through the subsurface.