Foodborne bacterial pathogens: genome-based approaches for enduring and emerging threats in a complex and changing world.

Foodborne illnesses pose a substantial health and economic burden, presenting challenges in prevention due to the diverse microbial hazards that can enter and spread within food systems. Various factors, including natural, political and commercial drivers, influence food production and distribution. The risks of foodborne illness will continue to evolve in step with these drivers and with changes to food systems. For example, climate impacts on water availability for agriculture, changes in food sustainability targets and evolving customer preferences can all have an impact on the ecology of foodborne pathogens and the agrifood niches that can carry microorganisms. Whole-genome and metagenome sequencing, combined with microbial surveillance schemes and insights from the food system, can provide authorities and businesses with transformative information to address risks and implement new food safety interventions across the food chain. In this Review, we describe how genome-based approaches have advanced our understanding of the evolution and spread of enduring bacterial foodborne hazards as well as their role in identifying emerging foodborne hazards. Furthermore, foodborne hazards exist in complex microbial communities across the entire food chain, and consideration of these co-existing organisms is essential to understanding the entire ecology supporting pathogen persistence and transmission in an evolving food system.

Contrasting long-term dynamics of antimicrobial resistance and virulence plasmids in Salmonella Typhimurium from animals.

Plasmids are mobile elements that can carry genes encoding traits of clinical concern, including antimicrobial resistance (AMR) and virulence. Population-level studies of Enterobacterales, including Escherichia coli, Shigella and Klebsiella, indicate that plasmids are important drivers of lineage expansions and dissemination of AMR genes. Salmonella Typhimurium is the second most common cause of salmonellosis in humans and livestock in the UK and Europe. The long-term dynamics of plasmids between S. Typhimurium were investigated using isolates collected through national surveillance of animals in England and Wales over a 25-year period. The population structure of S. Typhimurium and its virulence plasmid (where present) were inferred through phylogenetic analyses using whole-genome sequence data for 496 isolates. Antimicrobial resistance genes and plasmid markers were detected in silico. Phenotypic plasmid characterization, using the Kado and Liu method, was used to confirm the number and size of plasmids. The differences in AMR and plasmids between clades were striking, with livestock clades more likely to carry one or more AMR plasmid and be multi-drug-resistant compared to clades associated with wildlife and companion animals. Multiple small non-AMR plasmids were distributed across clades. However, all hybrid AMR-virulence plasmids and most AMR plasmids were highly clade-associated and persisted over decades, with minimal evidence of horizontal transfer between clades. This contrasts with the role of plasmids in the short-term dissemination of AMR between diverse strains in other Enterobacterales in high-antimicrobial-use settings, with implications for predicting plasmid dissemination amongst S. Typhimurium.

Antimicrobial Resistance Diversity Suggestive of Distinct Salmonella Typhimurium Sources or Selective Pressures in Food-Production Animals.

Salmonella enterica subsp. enterica serovar Typhimurium is a common cause of enterocolitis in humans globally, with multidrug resistant (MDR) strains posing an enhanced threat. S. Typhimurium is also a pathogen in food-production animals, and these populations can act as reservoirs of the bacterium. Therefore, surveillance and control measures within food-production animal populations are of importance both to animal and human health and have the potential to be enhanced though improved understanding of the epidemiology of S. Typhimurium within and between food-production animal populations. Here, data from Scotland and national surveillance England and Wales data for isolates from cattle (n = 1115), chickens (n = 248) and pigs (n = 2174) collected between 2003 and 2014 were analyzed. Ecological diversity analyses and rarefaction curves were used to compare the diversity of observed antimicrobial resistance (AMR) profiles between the host species, and within host species populations. Higher AMR profile diversity was observed in isolates from pigs compared to chickens across diversity measures and isolates from cattle for three of four diversity measures. Variation in AMR profile diversity between production sectors was noted, with higher AMR diversity of isolates from broiler compared to layer chickens, breeder compared to rearer and finisher pigs and beef compared to dairy cattle. Findings indicate variation in AMR profile diversity both within and between food-production animal host species. These observations suggest alternate sources of AMR bacteria and/or variation in selective evolutionary pressures within and between food-production animal host species populations.

Surveillance and Epidemiology of Drug Resistant Infections Consortium (SEDRIC): Supporting the transition from strategy to action.

In recognition of the central importance of surveillance and epidemiology in the control of antimicrobial resistance and the need to strengthen surveillance at all levels, Wellcome has brought together a new international expert group SEDRIC (Surveillance and Epidemiology of Drug Resistant Infections Consortium). SEDRIC aims to advance and transform the ways of tracking, sharing and analysing rates of infection and drug resistance, burden of disease, information on antibiotic use, opportunities for preventative measures such as vaccines, and contamination of the environment. SEDRIC will strengthen the availability of information needed to monitor and track risks, including an evaluation of access to, and utility of data generated by pharma and research activities, and will support the translation of surveillance data into interventions, changes in policy and more effective practices. Ways of working will include the provision of independent scientific analysis, advocacy and expert advice to groups, such as the Wellcome Drug Resistant Infection Priority Programme. A priority for SEDRIC's first Working Group is to review mechanisms to strengthen the generation, collection, collation and dissemination of high quality data, together with the need for creativity in the use of existing data and proxy measures, and linking to existing in-country networking infrastructure. SEDRIC will also promote the translation of technological innovations into public health solutions.

Detection of Rare Antimicrobial Resistance Profiles by Active and Passive Surveillance Approaches.

Antimicrobial resistance (AMR) surveillance systems are generally not specifically designed to detect emerging resistances and usually focus primarily on resistance to individual drugs. Evaluating the diversity of resistance, using ecological metrics, allows the assessment of sampling protocols with regard to the detection of rare phenotypes, comprising combinations of resistances. Surveillance data of phenotypic AMR of Canadian poultry Salmonella Heidelberg and swine Salmonella Typhimurium var. 5- were used to contrast active (representative isolates derived from healthy animals) and passive (diagnostic isolates) surveillance and assess their suitability for detecting emerging resistance patterns. Although in both datasets the prevalences of resistance to individual antimicrobials were not significantly different between the two surveillance systems, analysis of the diversity of entire resistance phenotypes demonstrated that passive surveillance of diagnostic isolates detected more unique phenotypes. Whilst the most appropriate surveillance method will depend on the relevant objectives, under the conditions of this study, passive surveillance of diagnostic isolates was more effective for the detection of rare and therefore potentially emerging resistance phenotypes.

Systems approaches to animal disease surveillance and resource allocation: methodological frameworks for behavioral analysis.

While demands for animal disease surveillance systems are growing, there has been little applied research that has examined the interactions between resource allocation, cost-effectiveness, and behavioral considerations of actors throughout the livestock supply chain in a surveillance system context. These interactions are important as feedbacks between surveillance decisions and disease evolution may be modulated by their contextual drivers, influencing the cost-effectiveness of a given surveillance system. This paper identifies a number of key behavioral aspects involved in animal health surveillance systems and reviews some novel methodologies for their analysis. A generic framework for analysis is discussed, with exemplar results provided to demonstrate the utility of such an approach in guiding better disease control and surveillance decisions.

Predicting the public health benefit of vaccinating cattle against Escherichia coli O157.

Identifying the major sources of risk in disease transmission is key to designing effective controls. However, understanding of transmission dynamics across species boundaries is typically poor, making the design and evaluation of controls particularly challenging for zoonotic pathogens. One such global pathogen is Escherichia coli O157, which causes a serious and sometimes fatal gastrointestinal illness. Cattle are the main reservoir for E. coli O157, and vaccines for cattle now exist. However, adoption of vaccines is being delayed by conflicting responsibilities of veterinary and public health agencies, economic drivers, and because clinical trials cannot easily test interventions across species boundaries, lack of information on the public health benefits. Here, we examine transmission risk across the cattle-human species boundary and show three key results. First, supershedding of the pathogen by cattle is associated with the genetic marker stx2. Second, by quantifying the link between shedding density in cattle and human risk, we show that only the relatively rare supershedding events contribute significantly to human risk. Third, we show that this finding has profound consequences for the public health benefits of the cattle vaccine. A naïve evaluation based on efficacy in cattle would suggest a 50% reduction in risk; however, because the vaccine targets the major source of human risk, we predict a reduction in human cases of nearly 85%. By accounting for nonlinearities in transmission across the human-animal interface, we show that adoption of these vaccines by the livestock industry could prevent substantial numbers of human E. coli O157 cases.

Implications of within-farm transmission for network dynamics: consequences for the spread of avian influenza.

The importance of considering coupled interactions across multiple population scales has not previously been studied for highly pathogenic avian influenza (HPAI) in the British commercial poultry industry. By simulating the within-flock transmission of HPAI using a deterministic S-E-I-R model, and by incorporating an additional environmental class representing infectious faeces, we tracked the build-up of infectious faeces within a poultry house over time. A measure of the transmission risk (TR) was computed for each farm by linking the amount of infectious faeces present each day of an outbreak with data describing the daily on-farm visit schedules for a major British catching company. Larger flocks tended to have greater levels of these catching-team visits. However, where density-dependent contact was assumed, faster outbreak detection (according to an assumed mortality threshold) led to a decreased opportunity for catching-team visits to coincide with an outbreak. For this reason, maximum TR-levels were found for mid-range flock sizes (~25,000-35,000 birds). When assessing all factors simultaneously using multivariable linear regression on the simulated outputs, those related to the pattern of catching-team visits had the largest effect on TR, with the most important movement-related factor depending on the mode of transmission. Using social network analysis on a further database to inform a measure of between-farm connectivity, we identified a large fraction of farms (28%) that had both a high TR and a high potential impact at the between farm level. Our results have counter-intuitive implications for between-farm spread that could not be predicted based on flock size alone, and together with further knowledge of the relative importance of transmission risk and impact, could have implications for improved targeting of control measures.

Using sequence data to identify alternative routes and risk of infection: a case-study of campylobacter in Scotland.

BACKGROUND: Genetic typing data are a potentially powerful resource for determining how infection is acquired. In this paper MLST typing was used to distinguish the routes and risks of infection of humans with Campylobacter jejuni from poultry and ruminant sources METHODS: C. jejuni samples from animal and environmental sources and from reported human cases confirmed between June 2005 and September 2006 were typed using MLST. The STRUCTURE software was used to assign the specific sequence types of the sporadic human cases to a particular source. We then used mixed case-case logistic regression analysis to compare the risk factors for being infected with C. jejuni from different sources. RESULTS: A total of 1,599 (46.3%) cases were assigned to poultry, 1,070 (31.0%) to ruminant and 67 (1.9%) to wild bird sources; the remaining 715 (20.7%) did not have a source that could be assigned with a probability of greater than 0.95. Compared to ruminant sources, cases attributed to poultry sources were typically among adults (odds ratio (OR) = 1.497, 95% confidence intervals (CIs) = 1.211, 1.852), not among males (OR = 0.834, 95% CIs = 0.712, 0.977), in areas with population density of greater than 500 people/km2 (OR = 1.213, 95% CIs = 1.030, 1.431), reported in the winter (OR = 1.272, 95% CIs = 1.067, 1.517) and had undertaken recent overseas travel (OR = 1.618, 95% CIs = 1.056, 2.481). The poultry assigned strains had a similar epidemiology to the unassigned strains, with the exception of a significantly higher likelihood of reporting overseas travel in unassigned strains. CONCLUSIONS: Rather than estimate relative risks for acquiring infection, our analyses show that individuals acquire C. jejuni infection from different sources have different associated risk factors. By enhancing our ability to identify at-risk groups and the times at which these groups are likely to be at risk, this work allows public health messages to be targeted more effectively. The rapidly increasing capacity to conduct genetic typing of pathogens makes such traced epidemiological analysis more accessible and has the potential to substantially enhance epidemiological risk factor studies.

An ecological approach to assessing the epidemiology of antimicrobial resistance in animal and human populations.

We examined long-term surveillance data on antimicrobial resistance (AMR) in Salmonella Typhimurium DT104 (DT104) isolates from concurrently sampled and sympatric human and animal populations in Scotland. Using novel ecological and epidemiological approaches to examine diversity, and phenotypic and temporal relatedness of the resistance profiles, we assessed the more probable source of resistance of these two populations. The ecological diversity of AMR phenotypes was significantly greater in human isolates than in animal isolates, at the resolution of both sample and population. Of 5200 isolates, there were 65 resistance phenotypes, 13 unique to animals, 30 unique to humans and 22 were common to both. Of these 22, 11 were identified first in the human isolates, whereas only five were identified first in the animal isolates. We conclude that, while ecologically connected, animals and humans have distinguishable DT104 communities, differing in prevalence, linkage and diversity. Furthermore, we infer that the sympatric animal population is unlikely to be the major source of resistance diversity for humans. This suggests that current policy emphasis on restricting antimicrobial use in domestic animals may be overly simplistic. While these conclusions pertain to DT104 in Scotland, this approach could be applied to AMR in other bacteria-host ecosystems.

The prevalences of Salmonella Genomic Island 1 variants in human and animal Salmonella Typhimurium DT104 are distinguishable using a Bayesian approach.

Throughout the 1990 s, there was an epidemic of multidrug resistant Salmonella Typhimurium DT104 in both animals and humans in Scotland. The use of antimicrobials in agriculture is often cited as a major source of antimicrobial resistance in pathogenic bacteria of humans, suggesting that DT104 in animals and humans should demonstrate similar prevalences of resistance determinants. Until very recently, only the application of molecular methods would allow such a comparison and our understanding has been hindered by the fact that surveillance data are primarily phenotypic in nature. Here, using large scale surveillance datasets and a novel Bayesian approach, we infer and compare the prevalence of Salmonella Genomic Island 1 (SGI1), SGI1 variants, and resistance determinants independent of SGI1 in animal and human DT104 isolates from such phenotypic data. We demonstrate differences in the prevalences of SGI1, SGI1-B, SGI1-C, absence of SGI1, and tetracycline resistance determinants independent of SGI1 between these human and animal populations, a finding that challenges established tenets that DT104 in domestic animals and humans are from the same well-mixed microbial population.

Generating social network data using partially described networks: an example informing avian influenza control in the British poultry industry.

BACKGROUND: Targeted sampling can capture the characteristics of more vulnerable sectors of a population, but may bias the picture of population level disease risk. When sampling network data, an incomplete description of the population may arise leading to biased estimates of between-host connectivity. Avian influenza (AI) control planning in Great Britain (GB) provides one example where network data for the poultry industry (the Poultry Network Database or PND), targeted large premises and is consequently demographically biased. Exposing the effect of such biases on the geographical distribution of network properties could help target future poultry network data collection exercises. These data will be important for informing the control of potential future disease outbreaks. RESULTS: The PND was used to compute between-farm association frequencies, assuming that farms sharing the same slaughterhouse or catching company, or through integration, are potentially epidemiologically linked. The fitted statistical models were extrapolated to the Great Britain Poultry Register (GBPR); this dataset is more representative of the poultry industry but lacks network information. This comparison showed how systematic biases in the demographic characterisation of a network, resulting from targeted sampling procedures, can bias the derived picture of between-host connectivity within the network. CONCLUSIONS: With particular reference to the predictive modeling of AI in GB, we find significantly different connectivity patterns across GB when network estimates incorporate the more demographically representative information provided by the GBPR; this has not been accounted for by previous epidemiological analyses. We recommend ranking geographical regions, based on relative confidence in extrapolated estimates, for prioritising further data collection. Evaluating whether and how the between-farm association frequencies impact on the risk of between-farm transmission will be the focus of future work.

Geographic determinants of reported human Campylobacter infections in Scotland.

BACKGROUND: Campylobacteriosis is the leading cause of bacterial gastroenteritis in most developed countries. People are exposed to infection from contaminated food and environmental sources. However, the translation of these exposures into infection in the human population remains incompletely understood. This relationship is further complicated by differences in the presentation of cases, their investigation, identification, and reporting; thus, the actual differences in risk must be considered alongside the artefactual differences. METHODS: Data on 33,967 confirmed Campylobacter infections in mainland Scotland between 2000 and 2006 (inclusive) that were spatially referenced to the postcode sector level were analysed. Risk factors including the Carstairs index of social deprivation, the easting and northing of the centroid of the postcode sector, measures of livestock density by species and population density were tested in univariate screening using a non-spatial generalised linear model. The NHS Health Board of the case was included as a random effect in this final model. Subsequently, a spatial generalised linear mixed model (GLMM) was constructed and age-stratified sensitivity analysis was conducted on this model. RESULTS: The spatial GLMM included the protective effects of the Carstairs index (relative risk (RR) = 0.965, 95% Confidence intervals (CIs) = 0.959, 0.971) and population density (RR = 0.945, 95% CIs = 0.916, 0.974. Following stratification by age group, population density had a significant protective effect (RR = 0.745, 95% CIs = 0.700, 0.792) for those under 15 but not for those aged 15 and older (RR = 0.982, 95% CIs = 0.951, 1.014). Once these predictors have been taken into account three NHS Health Boards remain at significantly greater risk (Grampian, Highland and Tayside) and two at significantly lower risk (Argyll and Ayrshire and Arran). CONCLUSIONS: The less deprived and children living in rural areas are at the greatest risk of being reported as a case of Campylobacter infection. However, this analysis cannot differentiate between actual risk and heterogeneities in individual reporting behaviour; nevertheless this paper has demonstrated that it is possible to explain the pattern of reported Campylobacter infections using both social and environmental predictors.

Qualitative risk assessment of the acquisition of Meticillin-resistant staphylococcus aureus in pet dogs.

This article presents a qualitative risk assessment of the acquisition of meticillin-resistant Staphylococcus aureus (MRSA) in pet dogs, representing an important first step in the exploration of risk of bidirectional MRSA transfer between dogs and humans. A conceptual model of the seven potential pathways for MRSA acquisition in a dog in any given 24-hour period was developed and the data available to populate that model were considered qualitatively. Humans were found to represent the most important source of MRSA for dogs in both community and veterinary hospital settings. The environment was found to be secondary to humans in terms of importance and other dogs less still. This study highlights some important methodological limitations of a technique that is heavily relied upon for qualitative risk assessments and applies a novel process, the use of relative risk ranking, to enable the generation of a defensible output using a matrix combination approach. Given the limitations of the prescribed methods as applied to the problem under consideration, further validation, or repudiation, of the findings contained herein is called for using a subsequent quantitative assessment.

Temporal and spatial patterns of bovine Escherichia coli O157 prevalence and comparison of temporal changes in the patterns of phage types associated with bovine shedding and human E. coli O157 cases in Scotland between 1998-2000 and 2002-2004.

BACKGROUND: Escherichia coli O157 is an important cause of acute diarrhoea, haemorrhagic colitis and, especially in children, haemolytic uraemic syndrome (HUS). Incidence rates for human E. coli O157 infection in Scotland are higher than most other United Kingdom, European and North American countries. Cattle are considered the main reservoir for E. coli O157. Significant associations between livestock related exposures and human infection have been identified in a number of studies. RESULTS: Animal Studies: There were no statistically significant differences (P = 0.831) in the mean farm-level prevalence between the two studies (SEERAD: 0.218 (95%CI: 0.141-0.32); IPRAVE: 0.205 (95%CI: 0.135-0.296)). However, the mean pat-level prevalence decreased from 0.089 (95%CI: 0.075-0.105) to 0.040 (95%CI: 0.028-0.053) between the SEERAD and IPRAVE studies respectively (P < 0.001). Highly significant (P < 0.001) reductions in mean pat-level prevalence were also observed in the spring, in the North East and Central Scotland, and in the shedding of phage type (PT) 21/28. Human Cases: Contrasting the same time periods, there was a decline in the overall comparative annual reported incidence of human cases as well as in all the major PT groups except 'Other' PTs. For both cattle and humans, the predominant phage type between 1998 and 2004 was PT21/28 comprising over 50% of the positive cattle isolates and reported human cases respectively. The proportion of PT32, however, was represented by few (<5%) of reported human cases despite comprising over 10% of cattle isolates. Across the two studies there were differences in the proportion of PTs 21/28, 32 and 'Other' PTs in both cattle isolates and reported human cases; however, only differences in the cattle isolates were statistically significant (P = 0.002). CONCLUSION: There was no significant decrease in the mean farm-level prevalence of E. coli O157 between 1998 and 2004 in Scotland, despite significant declines in mean pat-level prevalence. Although there were declines in the number of human cases between the two study periods, there is no statistically significant evidence that the overall rate (per 100,000 population) of human E. coli O157 infections in Scotland over the last 10 years has altered. Comparable patterns in the distribution of PTs 21/28 and 32 between cattle and humans support a hypothesized link between the bovine reservoir and human infections. This emphasizes the need to apply and improve methods to reduce bovine shedding of E. coli O157 in Scotland where rates appear higher in both cattle and human populations, than in other countries.

Assessing the convergence of Markov Chain Monte Carlo methods: an example from evaluation of diagnostic tests in absence of a gold standard.

The accessibility of Markov Chain Monte Carlo (MCMC) methods for statistical inference have improved with the advent of general purpose software. This enables researchers with limited statistical skills to perform Bayesian analysis. Using MCMC sampling to do statistical inference requires convergence of the MCMC chain to its stationary distribution. There is no certain way to prove convergence; it is only possible to ascertain when convergence definitely has not been achieved. These methods are rather subjective and not implemented as automatic safeguards in general MCMC software. This paper considers a pragmatic approach towards assessing the convergence of MCMC methods illustrated by a Bayesian analysis of the Hui-Walter model for evaluating diagnostic tests in the absence of a gold standard. The Hui-Walter model has two optimal solutions, a property which causes problems with convergence when the solutions are sufficiently close in the parameter space. Using simulated data we demonstrate tools to assess the convergence and mixing of MCMC chains using examples with and without convergence. Suggestions to remedy the situation when the MCMC sampler fails to converge are given. The epidemiological implications of the two solutions of the Hui-Walter model are discussed.

The Gamma-Poisson model as a statistical method to determine if micro-organisms are randomly distributed in a food matrix.

The Gamma-Poisson model, i.e., a Poisson distribution where the parameter lambda is Gamma distributed, has been suggested as a statistical method for determining whether or not micro-organisms are randomly distributed in a food matrix. In this study, we analyse the Gamma-Poisson model to explore some of the properties of the Gamma-Poisson model left unexplored by the previous study. The conclusion of our analysis is that the Gamma-Poisson model distinguishes poorly between variation at the Poisson level and the Gamma level. Estimated parameter values from simulated data-sets showed large variation around the true values, even for moderate sample sizes (n=100). Furthermore, at these sample sizes the likelihood ratio is not a good test statistic for discriminating between the Gamma-Poisson distribution and the Poisson distribution. Hence, to determine if data are randomly distributed, i.e., Poisson distributed, the Gamma-Poisson distribution is not a good choice. However, the ratio between variation at the Poisson level and the Gamma level does provide a measure of the amount of overdispersion.

Implementation of radiotelemetry in a lab-in-a-pill format.

A miniaturised lab-in-a-pill device has been produced incorporating a temperature and pH sensor with wireless communication using the 433.92 MHz ISM band. The device has been designed in order to enable real time in situ measurements in the gastrointestinal (GI) tract, and accordingly, issues concerning the resolution and accuracy of the data, and the lifetime of the device have been considered. The sensors, which will measure two key parameters reflecting the physiological environment in the GI (as indicators for disease) were both controlled by an application specific integrated circuit (ASIC). The data were sampled at 10-bit resolution prior to communication off chip as a single interleaved data stream. This incorporated a power saving serial bitstream data compression algorithm that was found to extend the service lifetime of the pill by 70%. An integrated on-off keying (OOK) radio transmitter was used to send the signal to a local receiver (base station), prior to acquisition on a computer. A permanent magnet was also incorporated in the device to enable non-visual tracking of the system. We report on the implementation of this device, together with an initial study sampling from within the porcine GI tract, showing that measurements from the lab-on-a-pill, in situ, was within 90% of literature values.

A programmable microsystem using system-on-chip for real-time biotelemetry.

A telemetry microsystem, including multiple sensors, integrated instrumentation and a wireless interface has been implemented. We have employed a methodology akin to that for System-on-Chip microelectronics to design an integrated circuit instrument containing several "intellectual property" blocks that will enable convenient reuse of modules in future projects. The present system was optimized for low-power and included mixed-signal sensor circuits, a programmable digital system, a feedback clock control loop and RF circuits integrated on a 5 mm x 5 mm silicon chip using a 0.6 microm, 3.3 V CMOS process. Undesirable signal coupling between circuit components has been investigated and current injection into sensitive instrumentation nodes was minimized by careful floor-planning. The chip, the sensors, a magnetic induction-based transmitter and two silver oxide cells were packaged into a 36 mm x 12 mm capsule format. A base station was built in order to retrieve the data from the microsystem in real-time. The base station was designed to be adaptive and timing tolerant since the microsystem design was simplified to reduce power consumption and size. The telemetry system was found to have a packet error rate of 10(-3) using an asynchronous simplex link. Trials in animal carcasses were carried out to show that the transmitter was as effective as a conventional RF device whilst consuming less power.

Spatial distribution of Escherichia coli O157-positive farms in Scotland.

Using a sample of 949 Scottish farms with finishing cattle, the spatial distribution of Escherichia coli O157-positive farms was investigated using disease mapping models. The overall prevalence of E. coli O157-positive farms was estimated as 22%. The regions used in this study were the 16 postcode areas of Scotland. For each region, the posterior relative risk (RR) was estimated as a model-based alternative to the saturated standardized morbidity ratio (SMR), i.e., the ratio between observed and expected cases in a region. Three Bayesian hierarchical models with generalized linear modeling of the area-specific risks were used to estimate the posterior relative risk of E. coli O157-positive farms in the postcode areas: a random-effects model incorporating only spatially uncorrelated heterogeneity; a model incorporating both spatially correlated and uncorrelated heterogeneity; and a pseudo-mixture model with unstructured correlation and a weighted mix of two variance components representing the spatial correlation and a jump structure. None of the models identified any areas with a significant increase or decrease in risk. The deviance information criteria slightly favored the simplest model (RR range: 0.92--1.09). However, this model appeared to smooth out more of the variation in the RR compared to the pseudo-mixture model, which gave a more informative pattern of the posterior relative risks (range: 0.81--1.22).