Helen E. Clough

Frequency and Spatial Distribution of Environmental Campylobacter spp.

ABSTRACT Humans are exposed to Campylobacter spp. in a range of sources via both food and environmental pathways. For this study, we explored the frequency and distribution of thermophilic Campylobacter spp. in a 10- by 10-km square rural area of Cheshire, United Kingdom. The area contains approximately 70, mainly dairy, farms and is used extensively for outdoor recreational activities. Campylobacter spp. were isolated from a range of environmental samples by use of a systematic sampling grid. Livestock (mainly cattle) and wildlife feces and environmental water and soil samples were cultured, and isolates were presumptively identified by standard techniques. These isolates were further characterized by PCR. Campylobacter jejuni was the most prevalent species in all animal samples, ranging from 11% in samples from nonavian wildlife to 36% in cattle feces, and was isolated from 15% of water samples. Campylobacter coli was commonly found in water (17%) and sheep (21%) samples, but rarely in other samples. Campylobacter lari was recovered from all sample types, with the exception of sheep feces, and was found in moderate numbers in birds (7%) and water (5%). Campylobacter hyointestinalis was only recovered from cattle (7%) and birds (1%). The spatial distribution and determinants of C. jejuni in cattle feces were examined by the use of model-based spatial statistics. The distribution was consistent with very localized within-farm or within-field transmission and showed little evidence of any larger-scale spatial dependence. We concluded that there is a potentially high risk of human exposure to Campylobacter spp., particularly C. jejuni, in the environment of our study area. The prevalence and likely risk posed by C. jejuni-positive cattle feces in the environment diminished as the fecal material aged. After we took into account the age of the fecal material, the absence or presence of rain, and the presence of bird feces, there was evidence of significant variation in the prevalence of C. jejuni-positive cattle feces between grazing fields but no evidence of spatial clustering beyond this resolution. The spatial pattern of C. jejuni is therefore consistent with that for an organism that is ubiquitous in areas contaminated with cattle feces, with a short-scale variation in infection intensity that cannot be explained solely by variations in the age of the fecal material. The observed pattern is not consistent with large-scale transmission attributable to watercourses, wildlife territories, or other geographical features that transcend field and farm boundaries.

A COMPARISON BETWEEN PARAMETRIC AND NON-PARAMETRIC APPROACHES TO THE ANALYSIS OF REPLICATED SPATIAL POINT PATTERNS

The paper compares non-parametric (design-based) and parametric (model-based) approaches to the analysis of data in the form of replicated spatial point patterns in two or more experimental groups. Basic questions for data of this kind concern estimating the properties of the underlying spatial point process within each experimental group, and comparing the properties between groups. A non-parametric approach, building on work by Diggle et. al. (1991), summarizes each pattern by an estimate of the reduced second moment measure or K-function (Ripley (1977)) and compares mean K-functions between experimental groups using a bootstrap testing procedure. A parametric approach fits particular classes of parametric model to the data, uses the model parameter estimates as summaries and tests for differences between groups by comparing fits with and without the assumption of common parameter values across groups. The paper discusses how either approach can be implemented in the specific context of a single-factor replicated experiment and uses simulations to show how the parametric approach can be more efficient when the underlying model assumptions hold, but potentially misleading otherwise.

Prevalence and genetic diversity of Campylobacter spp. in environmental water samples from a 100-square-kilometer predominantly dairy farming area.

ABSTRACT Water samples were taken systematically from a 100-km2 area of mainly dairy farmland in northwestern England and examined for Campylobacter spp. Pulsed-field gel electrophoresis-restriction fragment length polymorphism (PFGE-RFLP) and flaA strain typing of Campylobacter jejuni and Campylobacter coli isolates were done. Data on the water source and the adjacent environment were recorded and examined as explanatory variables. Campylobacter spp. were isolated from 40.5% (n = 119) of the water samples tested. C. jejuni was isolated from 14.3%, C. coli was isolated from 18.5%, and Campylobacter lari was isolated from 4.2% of the samples. Campylobacter hyointestinalis was not isolated from any water source. The difference in prevalence between water types (trough, running, and standing) was significant (P = 0.001). C. jejuni was the species most commonly isolated from trough-water and running-water sources, while C. coli was the most frequently isolated from standing water (P < 0.001). No association was found between the presence of Escherichia coli and that of Campylobacter spp. The final multivariable logistic regression model for Campylobacter spp. included the following variables: water source, soil type, aspect, and amount of cattle fecal material in the environment (fecal pat count). Strain typing demonstrated a diverse population of C. jejuni and the presence of a common C. coli flaA type that was widely distributed throughout the area. Most of the isolates within the common flaA type were discriminated by PFGE-RFLP. These findings suggest a possible role for environmental water in the epidemiology of Campylobacter spp. in a farming environment.

Carbamazepine versus Valproate Monotherapy for Epilepsy: A Meta-analysis

Summary:  Purpose: To provide an overview of the evidence comparing carbamazepine (CBZ) and valproate (VPA) monotherapy for epilepsy, investigating whether existing data support the current practice of preferring CBZ for partial‐onset and VPA for generalized‐onset seizures.

ECOLOGICAL DIFFERENCES AND COEXISTENCE IN A GUILD OF MICROPARASITES: BARTONELLA IN WILD RODENTS

The study of ecological differences among coexisting microparasites has been largely neglected, but it addresses important and unusual issues because there is no clear distinction in such cases between conventional (resource) and apparent competition. Here patterns in the population dynamics are examined for four species of Bartonella (bacterial parasites) coexisting in two wild rodent hosts, bank voles (Clethrionomys glareolus) and wood mice (Apodemus sylvaticus). Using generalized linear modeling and mixed effects models, we examine, for these four species, seasonal patterns and dependencies on host density (both direct and delayed) and, having accounted for these, any differences in prevalence between the two hosts. Whereas previous studies had failed to uncover species differences, here all four were different. Two, B. doshiae and B. taylorii, were more prevalent in wood mice, and one, B. birtlesii, was more prevalent in bank voles. B. birtlesii, B. grahamii, and B. taylorii peaked in prevalence in the fall, whereas B. doshiae peaked in spring. For B. birtlesii in bank voles, density dependence was direct, but for B. taylorii in wood mice density dependence was delayed. B. birtlesii prevalence in wood mice was related to bank vole density. The implications of these differences for species coexistence are discussed.

Is equine colic seasonal? Novel application of a model based approach

BackgroundColic is an important cause of mortality and morbidity in domesticated horses yet many questions about this condition remain to be answered. One such question is: does season have an effect on the occurrence of colic? Time-series analysis provides a rigorous statistical approach to this question but until now, to our knowledge, it has not been used in this context. Traditional time-series modelling approaches have limited applicability in the case of relatively rare diseases, such as specific types of equine colic. In this paper we present a modelling approach that respects the discrete nature of the count data and, using a regression model with a correlated latent variable and one with a linear trend, we explored the seasonality of specific types of colic occurring at a UK referral hospital between January 1995–December 2004.ResultsSix- and twelve-month cyclical patterns were identified for all colics, all medical colics, epiploic foramen entrapment (EFE), equine grass sickness (EGS), surgically treated and large colon displacement/torsion colic groups. A twelve-month cyclical pattern only was seen in the large colon impaction colic group. There was no evidence of any cyclical pattern in the pedunculated lipoma group. These results were consistent irrespective of whether we were using a model including latent correlation or trend. Problems were encountered in attempting to include both trend and latent serial dependence in models simultaneously; this is likely to be a consequence of a lack of power to separate these two effects in the presence of small counts, yet in reality the underlying physical effect is likely to be a combination of both.ConclusionThe use of a regression model with either an autocorrelated latent variable or a linear trend has allowed us to establish formally a seasonal component to certain types of colic presented to a UK referral hospital over a 10 year period. These patterns appeared to coincide with either times of managemental change or periods when horses are more likely to be intensively managed. Further studies are required to identify the determinants of the observed seasonality. Importantly, this type of regression model has applications beyond the study of equine colic and it may be useful in the investigation of seasonal patterns in other, relatively rare, conditions in all species.

The prevalence of antimicrobial-resistant Escherichia coli in sympatric wild rodents varies by season and host

Aims:  To investigate the prevalence and temporal patterns of antimicrobial resistance in wild rodents with no apparent exposure to antimicrobials.

Bayesian methods for estimating pathogen prevalence within groups of animals from faecal-pat sampling

Pathogens such as Escherichia coli O157:H7 and Campylobacter spp. have been implicated in outbreaks of food poisoning in the UK and elsewhere. Domestic animals and wildlife are important reservoirs for both of these agents, and cross-contamination from faeces is believed to be responsible for many human outbreaks. Appropriate parameterisation of quantitative microbial-risk models requires representative data at all levels of the food chain. Our focus in this paper is on the early stages of the food chain-specifically, sampling issues which arise at the farm level. We estimated animal-pathogen prevalence from faecal-pat samples using a Bayesian method which reflected the uncertainties inherent in the animal-level prevalence estimates. (Note that prevalence here refers to the percentage of animals shedding the bacteria of interest). The method offers more flexibility than traditional, classical approaches: it allows the incorporation of prior belief, and permits the computation of a variety of distributional and numerical summaries, analogues of which often are not available through a classical framework. The Bayesian technique is illustrated with a number of examples reflecting the effects of a diversity of assumptions about the underlying processes. The technique appears to be both robust and flexible, and is useful when defecation rates in infected and uninfected groups are unequal, where population size is uncertain, and also where the microbiological-test sensitivity is imperfect. We also investigated the determination of the sample size necessary for determining animal-level prevalence from pat samples to within a pre-specified degree of accuracy.

Vero-cytotoxigenic Escherichia coli O157 in pasteurized milk containers at the point of retail: a qualitative approach to exposure assessment

Dairies within the United Kingdom are classified into two groups, namely, off-farm and on-farm dairies (the latter often being small scale). We propose a model for the probability of milk sold as pasteurized reaching the point of retail contaminated with Vero-cytotoxigenic Escherichia coli (VTEC) O157 from each of these two pathways. We evaluate qualitatively the exposures inherent in each, and compare and contrast the two situations. The model framework is generic, in that it can in principle be used, with the relevant data modifications, to provide a qualitative assessment of the likely exposure from milk sold as pasteurized to any potentially milk-borne pathogenic organism. Furthermore, the methodological approaches presented are widely applicable in the microbial risk assessment field. The specific example presented will be of particular interest to the UK dairy and public health communities: we conclude that the exposure potential per liter consumed from milk processed in off-farm dairies is negligible, whereas the exposure potential per liter consumed from milk processed on-farm is low, but not sufficiently small to be regarded as negligible. We also identify areas of data sparsity, which need to be addressed for quantitative risk assessment to proceed, and highlight the critical points in the pasteurized milk production chain, which, in the event of a breakdown, have the potential to increase the risk to the consumer.

Quantifying exposure to Vero-cytotoxigenic Escherichia coli O157 in milk sold as pasteurized: A model-based approach

Milk sold as pasteurized has historically been implicated in the UK and worldwide as a vehicle for outbreaks of food-borne gastrointestinal disease, with a number of causative pathogenic organisms. One such organism is verocytotoxigenic Escherichia coli, or E. coli, O157 (VTEC O157). We present a quantitative assessment of likely exposure to VTEC O157 via milk sold as pasteurized in the UK. Particular interest in our assessment concerns whether there is any differential risk between milk which is processed in on- and off-farm dairies. We model the milk production chain from the farm through to the point of retail and make a comparison between these two production environments. Our model is an example of the Modular Process Risk Modelling (MPRM) approach and represents uncertainty and variability in input parameters using probability distributions. We conclude that milk processed on farm poses the comparatively greater risk, although that risk is still small.