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More, Simon John
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More, Simon John
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Now showing 1 - 10 of 145
- PublicationCurrent and future ethical challenges facing the veterinary profession in Ireland(University College Dublin, 2016-09)
; ; ; ; 148 - PublicationChallenges and solutions to support good equine welfare practice in Ireland(University College Dublin, 2010-06)
; ; ; ; 529 - PublicationModelling transmission of Mycobacterium avium subspecies paratuberculosis between Irish dairy cattle herds(Springer, 2022-06-22)
; ; ; ; Bovine paratuberculosis is an endemic disease caused by Mycobacterium avium subspecies paratuberculosis (Map). Map is mainly transmitted between herds through movement of infected but undetected animals. Our objective was to investigate the effect of observed herd characteristics on Map spread on a national scale in Ireland. Herd characteristics included herd size, number of breeding bulls introduced, number of animals purchased and sold, and number of herds the focal herd purchases from and sells to. We used these characteristics to classify herds in accordance with their probability of becoming infected and of spreading infection to other herds. A stochastic individual-based model was used to represent herd demography and Map infection dynamics of each dairy cattle herd in Ireland. Data on herd size and composition, as well as birth, death, and culling events were used to characterize herd demography. Herds were connected with each other through observed animal trade movements. Data consisted of 13 353 herds, with 4 494 768 dairy female animals, and 72 991 breeding bulls. We showed that the probability of an infected animal being introduced into the herd increases both with an increasing number of animals that enter a herd via trade and number of herds from which animals are sourced. Herds that both buy and sell a lot of animals pose the highest infection risk to other herds and could therefore play an important role in Map spread between herds.237 - PublicationEvaluation of national surveillance methods for detection of Irish dairy herds infected with Mycobacterium avium ssp. paratuberculosis(Elsevier, 2019-03)
; ; ; ; The aim of this study was to evaluate the utility and cost-effectiveness of a range of national surveillance methods for paratuberculosis in Irish dairy herds. We simulated alternative surveillance strategies applied to dairy cattle herds for the detection of Mycobacterium avium ssp. paratuberculosis (MAP)-infected herds (case-detection) or for estimation of confidence of herd freedom from infection (assurance testing). Strategies simulated included whole-herd milk or serum serology, serology on cull cows at slaughter, bulk milk tank serology, environmental testing, and pooled fecal testing. None of the strategies evaluated were ideal for widespread national case-detection surveillance. Herd testing with milk or serum ELISA or pooled fecal testing were the most effective methods currently available for detection of MAP-infected herds, with median herd sensitivity >60% and 100% herd specificity, although they are relatively expensive for widespread use. Environmental sampling shows promise as an alternative, with median herd sensitivity of 69%, but is also expensive unless samples can be pooled and requires further validation under Irish conditions. Bulk tank milk testing is the lowest cost option and may be useful for detecting high-prevalence herds but had median herd sensitivity <10% and positive predictive value of 85%. Cull cow sampling strategies were also lower cost but had median herd sensitivity <40% and herd positive predictive values of <50%, resulting in an increased number of test-positive herds, each of which requires follow-up herd testing to clarify status. Possible false-positive herd testing results associated with prior tuberculosis testing also presented logistical issues for both cull cow and bulk milk testing. Whole-herd milk or serum ELISA testing are currently the preferred testing strategies to estimate confidence of herd freedom from MAP in dairy herds due to the good technical performance and moderate cost of these strategies for individual herd testing. Cull cow serology and bulk tank milk sampling provide only minimal assurance value, with confidence of herd freedom increasing only minimally above the prior estimate. Different testing strategies should be considered when deciding on cost-effective approaches for case-detection compared with those used for building confidence of herd freedom (assurance testing) as part of a national program.150Scopus© Citations 21 - PublicationPrevalence and distribution of exposure to Schmallenberg virus in Irish cattle during November 2012 to November 2013(BioMed Central, 2015-10-20)
; ; ; ; Background: Schmallenberg virus (SBV) was first identified in November 2011. It is a novel Orthobunyavirus (family Bunyaviridae) whose main ill effect is congenital malformation of the musculoskeletal and central nervous systems. It is borne by Culicoides spp., and has spread extensively in western Europe. The first case of SBV in Ireland was diagnosed in October 2012. It was anticipated that once the virus emerged in Ireland that there would be wide scale or nationwide spread over the course of the 2013 vector season. The objectives of this study were to determine the seroprevalence and distribution of exposure to Schmallenberg virus in Irish cattle from November 2012 to November 2013. Methods: Samples of brain for the pathology based surveillance were collected from malformed bovine and ovine foetuses submitted for post mortem examination. These samples were tested for SBV using RT-qPCR. Three serological surveys were carried out on sera submitted for the national brucellosis eradicartion programme. A spatial analysis of both sets of data was carried out. Results: Between October 2012 and 10th May 2013, SBV was confirmed by RT-qPCR in brain tissues from malformed foetuses obtained from 49 cattle herds and 30 sheep flocks in Ireland. In national serosurveys conducted between November 2012 until November 2013 the herd-level and animal-level SBV seroprevalences in cattle were 53 and 36 % respectively for the first survey, 51 and 35 % for the second survey and 53 and 33 % for the third survey. The herd level seroprevalence in counties ranged from 0 to 100 %, with the counties in the south and southeast having the highest seroprevalence (>50 %), the midlands a moderate herd level seroprevalence (10–50 %) while northern and north western counties had a low herd level seroprevalence (0–10 %). There was close spatial agreement between the results of the two different targeted surveillance strategies. Conclusions: At the end of the 2012 vector season, there was widespread exposure to SBV among herds in southern and south eastern Ireland. During 2013, there was little or no evidence of further outward spread, unlike the situation in several other European countries. Given the lack of evidence for circulation of the virus since 2012, it is likely that the younger age cohort in herds previously exposed to SBV and substantial proportions of animals of all ages on the margins of affected areas are immunologically naïve to SBV, and would be susceptible to infection if the virus were to re-emerge.174Scopus© Citations 11 - PublicationHerd-level factors associated with detection of calves persistently infected with bovine viral diarrhoea virus (BVDV) in Irish cattle herds with negative herd status (NHS) during 2017A compulsory national BVD eradication programme commenced in Ireland in 2013. Since then considerable progress has been made, with the animal-level prevalence of calves born persistently infected (PI) falling from 0.67 % in 2013 to 0.06 % in 2018. The herd-level prevalence fell from 11.3 % in 2013 to 1.1 % in 2018. In the Irish programme, herds in which all animals have a known negative status and which have not contained any PI animals for 12 months or more are assigned a negative herd status (NHS). While considerable progress towards eradication has been made, PI calves have been identified in a small proportion of herds that had previously been assigned NHS. Given this context, a case-control study was conducted to investigate potential risk factors associated with loss of NHS in 2017. 546 herds which had NHS on 1 January 2017 and lost that status during 2017 (case herds) were matched with 2191 herds (control herds) that retained their NHS status throughout 2017. Previous history of BVD infection, herd size, herd expansion, the purchase of cattle including potential Trojan cattle and the density of BVD infection within 10 km of the herd emerged as significant factors in a multivariable logistic regression model. This work adds to the evidence base in support of the BVD eradication programme, particularly establishing why BVD re-emerged in herds which had been free of BVD for at least the previous 12 months prior to the identification of a BVD positive calf. This information will be especially important in the context of identifying herds which may be more likely to contain BVD positive animals once the programme moves to herd-based serology status for trading purposes in the post-eradication phase.
105Scopus© Citations 7 - PublicationGuidance Document on Scientific criteria for grouping chemicals into assessment groups for human risk assessment of combined exposure to multiple chemicals(Wiley, 2021-12)
; ; ; ; This guidance document provides harmonised and flexible methodologies to apply scientific criteria and prioritisation methods for grouping chemicals into assessment groups for human risk assessment of combined exposure to multiple chemicals. In the context of EFSA’s risk assessments, the problem formulation step defines the chemicals to be assessed in the terms of reference usually through regulatory criteria often set by risk managers based on legislative requirements. Scientific criteria such as hazard-driven criteria can be used to group these chemicals into assessment groups. In this guidance document, a framework is proposed to apply hazard-driven criteria for grouping of chemicals into assessment groups using mechanistic information on toxicity as the gold standard where available (i.e. common mode of action or adverse outcome pathway) through a structured weight of evidence approach. However, when such mechanistic data are not available, grouping may be performed using a common adverse outcome. Toxicokinetic data can also be useful for grouping, particularly when metabolism information is available for a class of compounds and common toxicologically relevant metabolites are shared. In addition, prioritisation methods provide means to identify low-priority chemicals and reduce the number of chemicals in an assessment group. Prioritisation methods include combined risk-based approaches, risk-based approaches for single chemicals and exposure-driven approaches. Case studies have been provided to illustrate the practical application of hazard-driven criteria and the use of prioritisation methods for grouping of chemicals in assessment groups. Recommendations for future work are discussed.43Scopus© Citations 18 - PublicationAfrican swine fever and outdoor farming of pigsThis opinion describes outdoor farming of pigs in the EU, assesses the risk of African swine fewer (ASF) introduction and spread associated with outdoor pig farms and proposes biosecurity and control measures for outdoor pig farms in ASF-affected areas of the EU. Evidence was collected from Member States (MSs) veterinary authorities, farmers’ associations, literature and legislative documents. An Expert knowledge elicitation (EKE) was carried out to group outdoor pig farms according to their risk of introduction and spread of ASF, to rank biosecurity measures regarding their effectiveness with regard to ASF and propose improvements of biosecurity for outdoor pig farming and accompanying control measures. Outdoor pig farming is common and various farm types are present throughout the EU. As there is no legislation at European level for categorising outdoor pig farms in the EU, information is limited, not harmonised and needs to be interpreted with care. The baseline risk of outdoor pig farms for ASFV introduction and its spread is high but with considerable uncertainty. The Panel is 66–90% certain that, if single solid or double fences were fully and properly implemented on all outdoor pig farms in areas of the EU where ASF is present in wild boar and in domestic pigs in indoor farms and outdoor farms (worst case scenario not considering different restriction zones or particular situations), without requiring any other outdoor-specific biosecurity measures or control measures, this would reduce the number of new ASF outbreaks occurring in these farms within a year by more than 50% compared to the baseline risk. The Panel concludes that the regular implementation of independent and objective on-farm biosecurity assessments using comprehensive standard protocols and approving outdoor pig farms on the basis of their biosecurity risk in an official system managed by competent authorities will further reduce the risk of ASF introduction and spread related to outdoor pig farms.
169 - PublicationChallenges and Solutions to Supporting Farm Animal Welfare in Ireland: Responding to the Human Element(Department of Agriculture, Food and the Marine, 2018-06-21)
; ; ; ; Over recent decades, changes in agriculture have pushed animal welfare as a topic of concern into mainstream public, policy and political conversations (Buller and Morris, 2003; Fraser, 2014; Broom, 2016). Despite the relationship between farmers and farm animals being important for farm animal welfare standards, there is limited understanding of how the nature of this relationship influences welfare outcomes. Understanding the complexities of this relationship and the wider context in which these complexities are situated is central to forming and implementing interventions that can be effective in improving farm animal welfare on individual farms.611 - PublicationA modelling framework for the prediction of the herd-level probability of infection from longitudinal data(Cold Spring Harbor Laboratory, 2021-09-01)
; ; ; ; The collective control programmes (CPs) that exist for many infectious diseases of farm animals rely on the application of diagnostic testing at regular time intervals for the identification of infected animals or herds. The diversity of these CPs complicates the trade of animals between regions or countries because the definition of freedom from infection differs from one CP to another. In this paper, we describe a statistical model for the prediction of herd-level probabilities of infection from longitudinal data collected as part of CPs against infectious diseases of cattle. The model was applied to data collected as part of a CP against bovine viral diarrhoea virus (BVDV) infection in Loire-Atlantique, France. The model represents infection as a herd latent status with a monthly dynamics. This latent status determines test results through test sensitivity and test specificity. The probability of becoming status positive between consecutive months is modelled as a function of risk factors (when available) using logistic regression. Modelling is performed in a Bayesian framework, using either Stan or JAGS. Prior distributions need to be provided for the sensitivities and specificities of the different tests used, for the probability of remaining status positive between months as well as for the probability of becoming positive between months. When risk factors are available, prior distributions need to be provided for the coefficients of the logistic regression, replacing the prior for the probability of becoming positive. From these prior distributions and from the longitudinal data, the model returns posterior probability distributions for being status positive for all herds on the current month. Data from the previous months are used for parameter estimation. The impact of using different prior distributions and model implementations on parameter estimation was evaluated. The main advantage of this model is its ability to predict a probability of being status positive in a month from inputs that can vary in terms of nature of test, frequency of testing and risk factor availability/presence. The main challenge in applying the model to the BVDV CP data was in identifying prior distributions, especially for test characteristics, that corresponded to the latent status of interest, i.e. herds with at least one persistently infected (PI) animal. The model is available on Github as an R package (https://github.com/AurMad/STOCfree) and can be used to carry out output-based evaluation of disease CPs.13