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P. Gale - One of the best experts on this subject based on the ideXlab platform.
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applications of omics approaches to the development of Microbiological Risk Assessment using rna virus dose response models as a case study
Journal of Applied Microbiology, 2014Co-Authors: P. Gale, A. Hill, J. Bassett, Peter Mcclure, Louise Kelly, Le Y Marc, I. SoumpasisAbstract:The last decade has seen a huge increase in the amount of 'omics' data available and in our ability to interpret those data. The aim of this paper was to consider how omics techniques can be used to improve and refine Microbiological Risk Assessment, using dose-response models for RNA viruses, with particular reference to norovirus through the oral route as the case study. The dose-response model for initial infection in the gastrointestinal tract is broken down into the component steps at the molecular level and the feasibility of assigning probabilities to each step assessed. The molecular mechanisms are not sufficiently well understood at present to enable quantitative estimation of probabilities on the basis of omics data. At present, the great strength of gene sequence data appears to be in giving information on the distribution and proportion of susceptible genotypes (for example due to the presence of the appropriate pathogen-binding receptor) in the host population rather than in predicting specificities from the amino acid sequences concurrently obtained. The nature of the mutant spectrum in RNA viruses greatly complicates the application of omics approaches to the development of mechanistic dose-response models and prevents prediction of Risks of disease progression (given infection has occurred) at the level of the individual host. However, molecular markers in the host and virus may enable more broad predictions to be made about the consequences of exposure in a population. In an alternative approach, comparing the results of deep sequencing of RNA viruses in the faeces/vomitus from donor humans with those from their infected recipients may enable direct estimates of the average probability of infection per virion to be made.
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Applications of omics approaches to the development of Microbiological Risk Assessment using RNA virus dose–response models as a case study
Journal of applied microbiology, 2014Co-Authors: P. Gale, A. Hill, Louise Anne Kelly, J. Bassett, Peter Mcclure, Y. Le Marc, I. SoumpasisAbstract:The last decade has seen a huge increase in the amount of “omics” data available and in our ability to interpret those data. The aim of this paper is to consider how omics techniques can be used to improve and refine Microbiological Risk Assessment, using dose response models for RNA viruses, with particular reference to norovirus through the oral route as the case study. The dose response model for initial infection in the gastrointestinal tract is broken down into the component steps at the molecular level and the feasibility of assigning probabilities to each step assessed. The molecular mechanisms are not sufficiently well understood at present to enable quantitative estimation of probabilities on the basis of omics data. At present, the great strength of gene sequence data appears to be in giving information on the distribution and proportion of susceptible genotypes (for example due to the presence of the appropriate pathogen-binding receptor) in the host population rather than in predicting specificities from the amino acid sequences concurrently obtained. The nature of the mutant spectrum in RNA viruses greatly complicates the application of omics approaches to development of mechanistic dose response models and prevents prediction of Risks of disease progression (given infection has occurred) at the level of the individual host. However, molecular markers in the host and virus may enable more broad predictions to be made about the consequences of exposure in a population. In an alternative approach, comparing the results of deep sequencing of RNA viruses in the faeces/vomitus from donor humans with those from their infected recipients may enable direct estimates of the average probability of infection per virion to be made.
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Developments in Microbiological Risk Assessment for drinking water
Journal of applied microbiology, 2001Co-Authors: P. GaleAbstract:1. SUMMARYThis paper considers the development of MicrobiologicalRisk Assessment models for pathogenic agents in drinkingwater with particular reference to Cryptosporidium parvum,rotavirus and bovine spongiform encephalopathy (BSE).The available evidence suggests that there is potential forconsiderable variation in exposures to C. parvum oocyststhrough drinking water, during both outbreak and non-outbreak conditions. This spatial/temporal heterogeneityarises both from variation in oocyst densities in the rawwater and fluctuations in the removal efficiencies of drinkingwater treatment. In terms of Risk prediction, modelling thevariation in doses ingested by individual drinking waterconsumers is not important if the dose–response curve islinear and the oocysts act independently during infection.Indeed, the total pathogen loading on the population asrepresented by the arithmetic mean exposure is sufficient forRisk prediction for C. parvum, BSE and other agents of lowinfectivity, providing the infecting particles (i.e. oocysts orBSE prions) are known to act independently. However, formore highly infectious agents, such as rotavirus, ignoring1. Summary, 1912. Introduction, 1922.1 Overview of the Risk Assessment approach, 1923. Pathogen exposures through drinking water, 1923.1 Pathogen exposures under non-outbreak condi-tions, 1933.1.1 Variation in micro-organism counts withinlarge volume samples, 1933.1.2 Effect of treatment on the spatial distribu-tion of micro-organisms, 1933.1.3 Implication for Cryptosporidium exposures todrinking water consumers under non-out-break conditions, 1953.2 A model for Cryptosporidium oocyst concentrationsin drinking water during an outbreak, 1964. Dose–response curves. Estimating the Risk to humansfrom ingesting low pathogen doses, 1974.1 Cryptosporidium parvum, 1974.1.1 Experiments with salmonellas in mice suggestthat pathogens act independently and do notco-operate during infection, 1984.1.2 Acquired protective immunity for Cryptospo-ridium parvum, 1994.1.3 Virulence of different strains of Cryptospori-dium parvum, 1994.2 Human rotavirus, 1994.3 Bovine spongiform encephalopathy, 2004.3.1 The human oral ID
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developments in Microbiological Risk Assessment models for drinking water a short review
Journal of Applied Microbiology, 1996Co-Authors: P. GaleAbstract:Microbiological Risk Assessment (MRA) is emerging method to predict the Risks of infection from waterborne pathogens (e.g. rotavirus and Cryptosporidium parvum) in the drinking water supply. The objectives of this paper are to review the appropriateness of current models, with emphasis on pathogen exposures through drinking water, and to consider the information necessary to further their development. Calculating pathogen exposures in MRA is currently limited by the fact that pathogen density data for drinking water supplies are only available for very large volume samples--much larger than imbibed daily by any consumer. To develop MRA, information is needed on how pathogens are dispersed within those volumes at the resolution of volumes typically consumed daily by individuals. Available evidence suggests that micro-organisms, including pathogens, are clustered to some degree, even within small volumes, exposing some drinking water consumers to much higher doses than others. By assuming pathogens are randomly dispersed, current models overestimate the Risk from the more infectious agents (e.g. rotaviruses) but underestimate the Risk from less infectious pathogens (e.g. C. parvum). Approaches to modelling pathogen densities in drinking water from source water data and treatment removal efficiencies require additional information on the degree to which treatment processes (e.g. filtration and coagulation) increase pathogen clustering. The missing information could be obtained from large-scale pilot plant studies.
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Developments in Microbiological Risk Assessment models for drinking water—a short review
The Journal of applied bacteriology, 1996Co-Authors: P. GaleAbstract:Microbiological Risk Assessment (MRA) is emerging method to predict the Risks of infection from waterborne pathogens (e.g. rotavirus and Cryptosporidium parvum) in the drinking water supply. The objectives of this paper are to review the appropriateness of current models, with emphasis on pathogen exposures through drinking water, and to consider the information necessary to further their development. Calculating pathogen exposures in MRA is currently limited by the fact that pathogen density data for drinking water supplies are only available for very large volume samples--much larger than imbibed daily by any consumer. To develop MRA, information is needed on how pathogens are dispersed within those volumes at the resolution of volumes typically consumed daily by individuals. Available evidence suggests that micro-organisms, including pathogens, are clustered to some degree, even within small volumes, exposing some drinking water consumers to much higher doses than others. By assuming pathogens are randomly dispersed, current models overestimate the Risk from the more infectious agents (e.g. rotaviruses) but underestimate the Risk from less infectious pathogens (e.g. C. parvum). Approaches to modelling pathogen densities in drinking water from source water data and treatment removal efficiencies require additional information on the degree to which treatment processes (e.g. filtration and coagulation) increase pathogen clustering. The missing information could be obtained from large-scale pilot plant studies.
I. Soumpasis - One of the best experts on this subject based on the ideXlab platform.
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applications of omics approaches to the development of Microbiological Risk Assessment using rna virus dose response models as a case study
Journal of Applied Microbiology, 2014Co-Authors: P. Gale, A. Hill, J. Bassett, Peter Mcclure, Louise Kelly, Le Y Marc, I. SoumpasisAbstract:The last decade has seen a huge increase in the amount of 'omics' data available and in our ability to interpret those data. The aim of this paper was to consider how omics techniques can be used to improve and refine Microbiological Risk Assessment, using dose-response models for RNA viruses, with particular reference to norovirus through the oral route as the case study. The dose-response model for initial infection in the gastrointestinal tract is broken down into the component steps at the molecular level and the feasibility of assigning probabilities to each step assessed. The molecular mechanisms are not sufficiently well understood at present to enable quantitative estimation of probabilities on the basis of omics data. At present, the great strength of gene sequence data appears to be in giving information on the distribution and proportion of susceptible genotypes (for example due to the presence of the appropriate pathogen-binding receptor) in the host population rather than in predicting specificities from the amino acid sequences concurrently obtained. The nature of the mutant spectrum in RNA viruses greatly complicates the application of omics approaches to the development of mechanistic dose-response models and prevents prediction of Risks of disease progression (given infection has occurred) at the level of the individual host. However, molecular markers in the host and virus may enable more broad predictions to be made about the consequences of exposure in a population. In an alternative approach, comparing the results of deep sequencing of RNA viruses in the faeces/vomitus from donor humans with those from their infected recipients may enable direct estimates of the average probability of infection per virion to be made.
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Applications of omics approaches to the development of Microbiological Risk Assessment using RNA virus dose–response models as a case study
Journal of applied microbiology, 2014Co-Authors: P. Gale, A. Hill, Louise Anne Kelly, J. Bassett, Peter Mcclure, Y. Le Marc, I. SoumpasisAbstract:The last decade has seen a huge increase in the amount of “omics” data available and in our ability to interpret those data. The aim of this paper is to consider how omics techniques can be used to improve and refine Microbiological Risk Assessment, using dose response models for RNA viruses, with particular reference to norovirus through the oral route as the case study. The dose response model for initial infection in the gastrointestinal tract is broken down into the component steps at the molecular level and the feasibility of assigning probabilities to each step assessed. The molecular mechanisms are not sufficiently well understood at present to enable quantitative estimation of probabilities on the basis of omics data. At present, the great strength of gene sequence data appears to be in giving information on the distribution and proportion of susceptible genotypes (for example due to the presence of the appropriate pathogen-binding receptor) in the host population rather than in predicting specificities from the amino acid sequences concurrently obtained. The nature of the mutant spectrum in RNA viruses greatly complicates the application of omics approaches to development of mechanistic dose response models and prevents prediction of Risks of disease progression (given infection has occurred) at the level of the individual host. However, molecular markers in the host and virus may enable more broad predictions to be made about the consequences of exposure in a population. In an alternative approach, comparing the results of deep sequencing of RNA viruses in the faeces/vomitus from donor humans with those from their infected recipients may enable direct estimates of the average probability of infection per virion to be made.
Peter Mcclure - One of the best experts on this subject based on the ideXlab platform.
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applications of omics approaches to the development of Microbiological Risk Assessment using rna virus dose response models as a case study
Journal of Applied Microbiology, 2014Co-Authors: P. Gale, A. Hill, J. Bassett, Peter Mcclure, Louise Kelly, Le Y Marc, I. SoumpasisAbstract:The last decade has seen a huge increase in the amount of 'omics' data available and in our ability to interpret those data. The aim of this paper was to consider how omics techniques can be used to improve and refine Microbiological Risk Assessment, using dose-response models for RNA viruses, with particular reference to norovirus through the oral route as the case study. The dose-response model for initial infection in the gastrointestinal tract is broken down into the component steps at the molecular level and the feasibility of assigning probabilities to each step assessed. The molecular mechanisms are not sufficiently well understood at present to enable quantitative estimation of probabilities on the basis of omics data. At present, the great strength of gene sequence data appears to be in giving information on the distribution and proportion of susceptible genotypes (for example due to the presence of the appropriate pathogen-binding receptor) in the host population rather than in predicting specificities from the amino acid sequences concurrently obtained. The nature of the mutant spectrum in RNA viruses greatly complicates the application of omics approaches to the development of mechanistic dose-response models and prevents prediction of Risks of disease progression (given infection has occurred) at the level of the individual host. However, molecular markers in the host and virus may enable more broad predictions to be made about the consequences of exposure in a population. In an alternative approach, comparing the results of deep sequencing of RNA viruses in the faeces/vomitus from donor humans with those from their infected recipients may enable direct estimates of the average probability of infection per virion to be made.
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Applications of omics approaches to the development of Microbiological Risk Assessment using RNA virus dose–response models as a case study
Journal of applied microbiology, 2014Co-Authors: P. Gale, A. Hill, Louise Anne Kelly, J. Bassett, Peter Mcclure, Y. Le Marc, I. SoumpasisAbstract:The last decade has seen a huge increase in the amount of “omics” data available and in our ability to interpret those data. The aim of this paper is to consider how omics techniques can be used to improve and refine Microbiological Risk Assessment, using dose response models for RNA viruses, with particular reference to norovirus through the oral route as the case study. The dose response model for initial infection in the gastrointestinal tract is broken down into the component steps at the molecular level and the feasibility of assigning probabilities to each step assessed. The molecular mechanisms are not sufficiently well understood at present to enable quantitative estimation of probabilities on the basis of omics data. At present, the great strength of gene sequence data appears to be in giving information on the distribution and proportion of susceptible genotypes (for example due to the presence of the appropriate pathogen-binding receptor) in the host population rather than in predicting specificities from the amino acid sequences concurrently obtained. The nature of the mutant spectrum in RNA viruses greatly complicates the application of omics approaches to development of mechanistic dose response models and prevents prediction of Risks of disease progression (given infection has occurred) at the level of the individual host. However, molecular markers in the host and virus may enable more broad predictions to be made about the consequences of exposure in a population. In an alternative approach, comparing the results of deep sequencing of RNA viruses in the faeces/vomitus from donor humans with those from their infected recipients may enable direct estimates of the average probability of infection per virion to be made.
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quantitative Microbiological Risk Assessment principles applied to determining the comparative Risk of salmonellosis from chicken products
Journal of Food Protection, 1998Co-Authors: Brown Martyn Hatton, Kenneth W Davies, Christelle M P Billon, Carol Adair, Peter McclureAbstract:Ensuring Microbiological safety requires identification of realistic hazards and the means of controlling them. The Risk Assessment framework proposed by Codex Alimentarius allows the impact of raw materials and processes to be appreciated, and the output can be used for Risk management and communication. Mathematical models allow numerical information to be processed by a computer and interpreted to give quantitative or comparative Risk Assessments. In this example, models have been put together according to the Codex. Alimentarius principles, providing a quantitative Risk Assessment (QRA) of salmonellosis from frozen poultry products. This model-based QRA takes into account three types of information: occurrence and distribution of the agent, sensitivity of populations to infection (e.g., normal or susceptible), and the effect of cooking (in the factory or home) on concentration of the agent and hence Risks of infection after product consumption. It only demonstrates the impact of a single-process step (heating) and the effect of changes in population sensitivity, raw material quality, and cooking regime on the final Risk. The effects of growth and recontamination are not considered. To aid Risk communication, the models have been visualized by means of displays and slider controls on a computer screen because effective communication is essential to encourage manufacturers and their product designers to assess the effect of changes in processing or materials on Risk.
Eric G. Evers - One of the best experts on this subject based on the ideXlab platform.
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Modelling and magnitude estimation of cross-contamination in the kitchen for quantitative Microbiological Risk Assessment (QMRA).
EFSA journal. European Food Safety Authority, 2020Co-Authors: Maria Francesca Iulietto, Eric G. EversAbstract:In the kitchen of the consumer, two main transmission routes are relevant for quantitative Microbiological Risk Assessment (QMRA): the cross-contamination route, where a pathogen on a food product may evade heating by transmission via hands, kitchen utensils and other surfaces, e.g. to non-contaminated products to be consumed raw; and the heating route, where pathogens remain on the food product and are for the most part inactivated through heating. This project was undertaken to model and estimate the magnitude of cross-contamination in the domestic environment. Scientific information from the relevant literature was collected and analyzed, to define the cross-contamination routes, to describe the variability sources and to extract and harmonise the transfer fractions to be included as model parameters. The model was used to estimate the relative impact of the cross-contamination routes for different scenarios. In addition, the effectiveness of several interventions in reducing the Risk of food-borne diseases due to cross-contamination was investigated. The outputs of the model showed that the cutting board route presents a higher impact compared to other routes and replacement of the kitchen utensils is more effective than other interventions investigated; the transfer to other surfaces and objects, which can house bacteria in the environment, is also described. Laboratory cross-contamination trials have been performed to estimate bacterial transfer via cutting, from the external surface of the meat to the cutting surfaces and to the knife. The results, obtained from the laboratory trials, show magnitudes of and differences in the bacterial transfer fraction to the knife and the cutting surface in relation to which side of the meat is contaminated. Despite the complexity of factors which influence bacterial transfer, the combination of laboratory work with mathematical modelling enhanced scientific understanding and appreciation of the uncertainty of the estimates. QMRA methodology results in magnitude estimation of cross-contamination in the kitchen and evaluation of intervention strategies.
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Improved swift Quantitative Microbiological Risk Assessment (sQMRA) methodology
Food Control, 2017Co-Authors: Jurgen E. Chardon, Eric G. EversAbstract:Abstract We developed an improved simplified Quantitative Microbiological Risk Assessment (QMRA) model and tool with reduced data need, applicable to any pathogen - food product combination and in addition suitable for basic QMRA education. The swift QMRA (sQMRA2) – model follows pathogen numbers through part of the food chain, starting at the retail phase, and ends with the estimated number of human cases of illness. The accompanying tool was implemented in Excel/@Risk. Relative Risk (compared to other pathogen-food product combinations) rather than absolute Risk was considered the most useful model output. The model includes storage at home (categories: room/fridge/freezer), cross-contamination (yes/no) and heating (done/undercooked/raw) during preparation in the kitchen and a dose response relationship (Binomial/Beta-Binomial). The model also includes variability, e.g. of pathogen concentration and food product heating (time, temperature) in the kitchen. The general setup of the sQMRA2 tool consists of 14 consecutive (sets of) questions for values of parameters and per phase detailed intermediate model output broken down into categories. On a separate sheet, attribution of storage, cross-contamination and heating transmission routes in terms of exposure (probability of a contaminated portion, number of cfu) and number of human cases are presented. Further, intermediate exposures (number of contaminated portions, number of cfu) and final Risks (number of human cases, DALYs, cost of illness), relative as well as absolute, are given. sQMRA2 is useful for quickly obtaining relative public health Risk QMRA estimates of multiple pathogen - food combinations, which can be directly useful for Risk management in terms of attribution or for the selection of high Risk candidates for the application of extensive QMRA. It is also useful for educational purposes because of the insightful presentation of intermediate and final model output. As an example, sQMRA2 calculations were given for Campylobacter and Salmonella in chicken fillet, filet americain and table eggs.
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A Quantitative Microbiological Risk Assessment for Salmonella in Pigs for the European Union
Risk analysis : an official publication of the Society for Risk Analysis, 2016Co-Authors: Emma Snary, Eric G. Evers, Robin R. L. Simons, Arno N. Swart, Håkan Vigre, Ana Rita Coutinho Calado Domingues, Tine Hald, A. HillAbstract:A farm-to-consumption quantitative Microbiological Risk Assessment (QMRA) for Salmonella in pigs in the European Union has been developed for the European Food Safety Authority. The primary aim of the QMRA was to assess the impact of hypothetical reductions of slaughter-pig prevalence and the impact of control measures on the Risk of human Salmonella infection. A key consideration during the QMRA development was the characterization of variability between E.U. Member States (MSs), and therefore a generic MS model was developed that accounts for differences in pig production, slaughterhouse practices, and consumption patterns. To demonstrate the parameterization of the model, four case study MSs were selected that illustrate the variability in production of pork meat and products across MSs. For the case study MSs the average probability of illness was estimated to be between 1 in 100,000 and 1 in 10 million servings given consumption of one of the three product types considered (pork cuts, minced meat, and fermented ready-to-eat sausages). Further analyses of the farm-to-consumption QMRA suggest that the vast majority of human Risk derives from infected pigs with a high concentration of Salmonella in their feces (≥10(4) CFU/g). Therefore, it is concluded that interventions should be focused on either decreasing the level of Salmonella in the feces of infected pigs, the introduction of a control step at the abattoir to reduce the transfer of feces to the exterior of the pig, or a control step to reduce the level of Salmonella on the carcass post-evisceration.
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A quantitative Microbiological Risk Assessment for Campylobacter in petting zoos.
Risk analysis : an official publication of the Society for Risk Analysis, 2014Co-Authors: Eric G. Evers, Petra A. Berk, Mijke L. Horneman, Frans M. Van Leusden, Robert De JongeAbstract:The significance of petting zoos for transmission of Campylobacter to humans and the effect of interventions were estimated. A stochastic QMRA model simulating a child or adult visiting a Dutch petting zoo was built. The model describes the transmission of Campylobacter in animal feces from the various animal species, fences, and the playground to ingestion by visitors through touching these so-called carriers and subsequently touching their lips. Extensive field and laboratory research was done to fulfill data needs. Fecal contamination on all carriers was measured by swabbing in 10 petting zoos, using Escherichia coli as an indicator. Carrier-hand and hand-lip touching frequencies were estimated by, in total, 13 days of observations of visitors by two observers at two petting zoos. The transmission from carrier to hand and from hand to lip by touching was measured using preapplied cow feces to which E. coli WG5 was added as an indicator. Via a Beta-Poisson dose-response function, the number of Campylobacter cases for the whole of the Netherlands (16 million population) in a year was estimated at 187 and 52 for children and adults, respectively, so 239 in total. This is significantly lower than previous QMRA results on chicken fillet and drinking water consumption. Scenarios of 90% reduction of the contamination (meant to mimic cleaning) of all fences and just goat fences reduces the number of cases by 82% and 75%, respectively. The model can easily be adapted for other fecally transmitted pathogens.
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A Quantitative Microbiological Risk Assessment for Salmonella transmission in pigs in individual EU Member States
International Conference on the Epidemiology and Control of Biological Chemical and Physical Hazards in Pigs and Pork, 2011Co-Authors: A. Hill, Eric G. Evers, Emma Snary, Robin R. L. Simons, Arno N. Swart, Håkan Vigre, Ana Rita Coutinho Calado Domingues, Tine Hald, J. Tennant, S. DenmanAbstract:A farm-to-consumption quantitative Microbiological Risk Assessment (QMRA) for Salmonella in pigs has been developed for the European Food Safety Authority. The primary aim of the QMRA was to assess the impact of reductions of slaughterpig prevalence and the impact of important control measures applied at the farm and during transport, lairage and slaughter on the number of human cases of salmonellosis. The QMRA estimates the Risk of salmonellosis and number of human cases for three product types: pork cuts, minced meat and fermented ready-to-eat sausages. For four case study European Union Member States (MSs) the average probability of illness was estimated to be between 1 in 100,000 and 1 in 10 million servings given consumption of one of the three product types. The total numbers of cases attributable to the three product types was also estimated. The results from the intervention analysis suggest that specific slaughterhouse interventions are currently best placed to produce consistently large reductions in the number of human cases and that for high breeding prevalence MSs reducing infection on breeder farms would seem to be an important on-farm control measure.
A. Hill - One of the best experts on this subject based on the ideXlab platform.
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A Quantitative Microbiological Risk Assessment for Salmonella in Pigs for the European Union
Risk analysis : an official publication of the Society for Risk Analysis, 2016Co-Authors: Emma Snary, Eric G. Evers, Robin R. L. Simons, Arno N. Swart, Håkan Vigre, Ana Rita Coutinho Calado Domingues, Tine Hald, A. HillAbstract:A farm-to-consumption quantitative Microbiological Risk Assessment (QMRA) for Salmonella in pigs in the European Union has been developed for the European Food Safety Authority. The primary aim of the QMRA was to assess the impact of hypothetical reductions of slaughter-pig prevalence and the impact of control measures on the Risk of human Salmonella infection. A key consideration during the QMRA development was the characterization of variability between E.U. Member States (MSs), and therefore a generic MS model was developed that accounts for differences in pig production, slaughterhouse practices, and consumption patterns. To demonstrate the parameterization of the model, four case study MSs were selected that illustrate the variability in production of pork meat and products across MSs. For the case study MSs the average probability of illness was estimated to be between 1 in 100,000 and 1 in 10 million servings given consumption of one of the three product types considered (pork cuts, minced meat, and fermented ready-to-eat sausages). Further analyses of the farm-to-consumption QMRA suggest that the vast majority of human Risk derives from infected pigs with a high concentration of Salmonella in their feces (≥10(4) CFU/g). Therefore, it is concluded that interventions should be focused on either decreasing the level of Salmonella in the feces of infected pigs, the introduction of a control step at the abattoir to reduce the transfer of feces to the exterior of the pig, or a control step to reduce the level of Salmonella on the carcass post-evisceration.
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applications of omics approaches to the development of Microbiological Risk Assessment using rna virus dose response models as a case study
Journal of Applied Microbiology, 2014Co-Authors: P. Gale, A. Hill, J. Bassett, Peter Mcclure, Louise Kelly, Le Y Marc, I. SoumpasisAbstract:The last decade has seen a huge increase in the amount of 'omics' data available and in our ability to interpret those data. The aim of this paper was to consider how omics techniques can be used to improve and refine Microbiological Risk Assessment, using dose-response models for RNA viruses, with particular reference to norovirus through the oral route as the case study. The dose-response model for initial infection in the gastrointestinal tract is broken down into the component steps at the molecular level and the feasibility of assigning probabilities to each step assessed. The molecular mechanisms are not sufficiently well understood at present to enable quantitative estimation of probabilities on the basis of omics data. At present, the great strength of gene sequence data appears to be in giving information on the distribution and proportion of susceptible genotypes (for example due to the presence of the appropriate pathogen-binding receptor) in the host population rather than in predicting specificities from the amino acid sequences concurrently obtained. The nature of the mutant spectrum in RNA viruses greatly complicates the application of omics approaches to the development of mechanistic dose-response models and prevents prediction of Risks of disease progression (given infection has occurred) at the level of the individual host. However, molecular markers in the host and virus may enable more broad predictions to be made about the consequences of exposure in a population. In an alternative approach, comparing the results of deep sequencing of RNA viruses in the faeces/vomitus from donor humans with those from their infected recipients may enable direct estimates of the average probability of infection per virion to be made.
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Applications of omics approaches to the development of Microbiological Risk Assessment using RNA virus dose–response models as a case study
Journal of applied microbiology, 2014Co-Authors: P. Gale, A. Hill, Louise Anne Kelly, J. Bassett, Peter Mcclure, Y. Le Marc, I. SoumpasisAbstract:The last decade has seen a huge increase in the amount of “omics” data available and in our ability to interpret those data. The aim of this paper is to consider how omics techniques can be used to improve and refine Microbiological Risk Assessment, using dose response models for RNA viruses, with particular reference to norovirus through the oral route as the case study. The dose response model for initial infection in the gastrointestinal tract is broken down into the component steps at the molecular level and the feasibility of assigning probabilities to each step assessed. The molecular mechanisms are not sufficiently well understood at present to enable quantitative estimation of probabilities on the basis of omics data. At present, the great strength of gene sequence data appears to be in giving information on the distribution and proportion of susceptible genotypes (for example due to the presence of the appropriate pathogen-binding receptor) in the host population rather than in predicting specificities from the amino acid sequences concurrently obtained. The nature of the mutant spectrum in RNA viruses greatly complicates the application of omics approaches to development of mechanistic dose response models and prevents prediction of Risks of disease progression (given infection has occurred) at the level of the individual host. However, molecular markers in the host and virus may enable more broad predictions to be made about the consequences of exposure in a population. In an alternative approach, comparing the results of deep sequencing of RNA viruses in the faeces/vomitus from donor humans with those from their infected recipients may enable direct estimates of the average probability of infection per virion to be made.
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A Quantitative Microbiological Risk Assessment for Salmonella transmission in pigs in individual EU Member States
International Conference on the Epidemiology and Control of Biological Chemical and Physical Hazards in Pigs and Pork, 2011Co-Authors: A. Hill, Eric G. Evers, Emma Snary, Robin R. L. Simons, Arno N. Swart, Håkan Vigre, Ana Rita Coutinho Calado Domingues, Tine Hald, J. Tennant, S. DenmanAbstract:A farm-to-consumption quantitative Microbiological Risk Assessment (QMRA) for Salmonella in pigs has been developed for the European Food Safety Authority. The primary aim of the QMRA was to assess the impact of reductions of slaughterpig prevalence and the impact of important control measures applied at the farm and during transport, lairage and slaughter on the number of human cases of salmonellosis. The QMRA estimates the Risk of salmonellosis and number of human cases for three product types: pork cuts, minced meat and fermented ready-to-eat sausages. For four case study European Union Member States (MSs) the average probability of illness was estimated to be between 1 in 100,000 and 1 in 10 million servings given consumption of one of the three product types. The total numbers of cases attributable to the three product types was also estimated. The results from the intervention analysis suggest that specific slaughterhouse interventions are currently best placed to produce consistently large reductions in the number of human cases and that for high breeding prevalence MSs reducing infection on breeder farms would seem to be an important on-farm control measure.