Victor J. Del Rio Vilas

Within-holding prevalence of sheep classical scrapie in Great Britain.

BackgroundData from the Compulsory Scrapie Flocks Scheme (CSFS), part of the compulsory eradication measures for the control of scrapie in the EU, have been used to estimate the within-holding prevalence of classical scrapie in Great Britain (GB). Specifically data from one of the testing routes within the CSFS have been used; the initial cull (IC), whereby two options can be applied: the whole flock cull option by which the entire flock is depopulated, and the genotyping and cull of certain genotypes.ResultsBetween April 2005 and September 2007, 25,316 suitable samples, submitted from 411 flocks in 213 scrapie-affected holdings in Great Britain, were tested for scrapie. The predicted within-holding prevalence for the initial cull was 0.65% (95% CI: 0.55–0.75). For the whole cull option was 0.47% (95% CI: 0.32–0.68) and for the genotype and cull or mixed option (both options applied in different flocks of the same holding), the predicted within-holding prevalence was 0.7% (95% CI: 0.6–0.83). There were no significant differences in the within-flock prevalence between countries (England, Scotland and Wales) or between CSFS holdings by the surveillance stream that detected the index case. The number of CSFS flocks on a holding did not affect the overall within-holding prevalence of classical scrapie.ConclusionThese estimates are important in the discussion of the epidemiological implications of the current EU testing programme of scrapie-affected flocks and to inform epidemiological and mathematical models. Furthermore, these estimates may provide baseline data to assist the design of future surveillance activities and control policies with the aim to increase their efficiency.

Demographic risk factors for classical and atypical scrapie in Great Britain.

Following the bovine spongiform encephalopathy (BSE) crisis, the European Union has introduced policies for eradicating transmissible spongiform encephalopathies (TSEs), including scrapie, from large ruminants. However, recent European Union surveillance has identified a novel prion disease, ‘atypical’ scrapie, substantially different from classical scrapie. It is unknown whether atypical scrapie is naturally transmissible or zoonotic, like BSE. Furthermore, cases have occurred in scrapie-resistant genotypes that are targets for selection in legislated selective breeding programmes. Here, the first epidemiological study of British cases of atypical scrapie is described, focusing on the demographics and trading patterns of farms and using databases of recorded livestock movements. Triplet comparisons found that farms with atypical scrapie stock more sheep than those of the general, non-affected population. They also move larger numbers of animals than control farms, but similar numbers to farms reporting classical scrapie. Whilst there is weak evidence of association through sheep trading of farms reporting classical scrapie, atypical scrapie shows no such evidence, being well-distributed across regions of Great Britain and through the sheep-trading network. Thus, although cases are few in number so far, our study suggests that, should natural transmission of atypical scrapie be occurring at all, it is doing so slowly.

An integrated process and management tools for ranking multiple emerging threats to animal health

The UKs Department for Environment, Food and Rural Affairs supports the use of systematic tools for the prioritisation of known and well defined animal diseases to facilitate long and medium term planning of surveillance and disease control activities. The recognition that emerging events were not covered by the existing disease-specific approaches led to the establishment of the Veterinary Risk Group (VRG), constituted of government officials, and supporting structures such as the Risk Management Cycle and the Emerging Threat Highlight Report (ETHiR), to facilitate the identification, reporting and assessment of emerging threats to UKs animal health. Since its inception in November 2009 to the end of February 2011, the VRG reviewed 111 threats and vulnerabilities (T&V) reported through ETHiR. In July 2010 a decision support system (DSS) based on multi-criteria-decision-analysis (MCDA) improved ETHiR to allow the systematic prioritisation of emerging T&V. The DSS allows the regular ranking of emerging T&V by calculating a set of measurement indices related to the actual impact, possible impact on public perception and level of available capabilities associated with every T&V. The systematic characterisation of the processes leading to the assessment of T&V by the VRG has led to a consistent, auditable and transparent approach to the identification and assessment of emerging risks. The regular use of MCDA to manage a portfolio of emerging risks represents a different and novel application of MCDA in a health related context.

Estimating the hidden number of scrapie affected holdings in Great Britain using a simple, truncated count model allowing for heterogeneity

None of the current surveillance streams monitoring the presence of scrapie in Great Britain provide a comprehensive and unbiased estimate of the prevalence of the disease at the holding level. Previous work to estimate the under-ascertainment adjusted prevalence of scrapie in Great Britain applied multiple-list capture-recapture methods. The enforcement of new control measures on scrapie-affected holdings in 2004 has stopped the overlapping between surveillance sources and, hence, the application of multiple-list capture-recapture models. Alternative methods, still under the capture-recapture methodology, relying on repeated entries in one single list have been suggested in these situations. In this article, we apply one-list capture-recapture approaches to data held on the Scrapie Notifications Database to estimate the undetected population of scrapie-affected holdings with clinical disease in Great Britain for the years 2002, 2003, and 2004. For doing so, we develop a new diagnostic tool for indication of heterogeneity as well as a new understanding of the Zelterman and Chao’s lower bound estimators to account for potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a special, locally truncated Poisson likelihood equivalent to a binomial likelihood. This understanding allows the extension of the Zelterman approach by means of logistic regression to include observed heterogeneity in the form of covariates—in case studied here, the holding size and country of origin. Our results confirm the presence of substantial unobserved heterogeneity supporting the application of our two estimators. The total scrapie-affected holding population in Great Britain is around 300 holdings per year. None of the covariates appear to inform the model significantly.

Classical sheep scrapie in Great Britain: spatial analysis and identification of environmental and farm-related risk factors

BackgroundPrevious studies suggest that the spatial distribution of classical sheep scrapie in Great Britain is uneven and that certain flock characteristics may be associated with occurrence of the disease. However, the existence of areas of high and low disease-risk may also result from differences in the spatial distribution of environmental characteristics. In this study we explored the spatial pattern of classical scrapie in Great Britain between 2002 and 2005 and investigated the association between disease occurrence and various environmental and farm-related risk factors.ResultsExploratory spatial analysis: South Wales was found to have a higher density of scrapie-positive farms than the rest of Great Britain. In addition, a small cluster of high-risk farms was identified in the center of this region in which clustering of scrapie-positive farms occurred up to a distance of approximately 40 km.Spatial modelling: A mixed-effects regression model identified flock-size and soil drainage to be significantly associated with the occurrence of scrapie in England and Wales (area under the curve (AUC) 0.71 ± 0.01, 95% CI 0.68 - 0.74). The predictive risk map based on the estimated association between these factors and disease occurrence showed most of Wales to be at risk of being confirmed positive for scrapie with areas of highest risk in central and south Wales. In England, areas with the highest risk occurred mainly in the north and the midlands.ConclusionThe observed distribution of scrapie in Great Britain exhibited a definite spatial pattern with south Wales identified as an area of high occurrence. In addition both flock (flock size) and environmental variables (soil drainage) were found to be significantly associated with the occurrence of the disease. However, the models AUC indicated unexplained variation remaining in the model and the source of this variation may lie in farm-level characteristics rather than spatially-varying ones such as environmental factors.

A comparison of the active surveillance of scrapie in the European Union

The abattoir and the fallen stock surveys constitute the active surveillance component aimed at improving the detection of scrapie across the European Union. Previous studies have suggested the occurrence of significant differences in the operation of the surveys across the EU. In the present study we assessed the standardisation of the surveys throughout time across the EU and identified clusters of countries with similar underlying characteristics allowing comparisons between them. In the absence of sufficient covariate information to explain the observed variability across countries, we modelled the unobserved heterogeneity by means of non-parametric distributions on the risk ratios of the fallen stock over the abattoir survey. More specifically, we used the profile likelihood method on 2003, 2004 and 2005 active surveillance data for 18 European countries on classical scrapie, and on 2004 and 2005 data for atypical scrapie separately. We extended our analyses to include the limited covariate information available, more specifically, the proportion of the adult sheep population sampled by the fallen stock survey every year. Our results show that the between-country heterogeneity dropped in 2004 and 2005 relative to that of 2003 for classical scrapie. As a consequence, the number of clusters in the last two years was also reduced indicating the gradual standardisation of the surveillance efforts across the EU. The crude analyses of the atypical data grouped all the countries in one cluster and showed non-significant gain in the detection of this type of scrapie by any of the two sources. The proportion of the population sampled by the fallen stock appeared significantly associated with our risk ratio for both types of scrapie, although in opposite directions: negative for classical and positive for atypical. The initial justification for the fallen stock, targeting a high-risk population to increase the likelihood of case finding, appears compromised for both types of scrapie in some countries.

Explaining the heterogeneous scrapie surveillance figures across Europe: a meta-regression approach

BackgroundTwo annual surveys, the abattoir and the fallen stock, monitor the presence of scrapie across Europe. A simple comparison between the prevalence estimates in different countries reveals that, in 2003, the abattoir survey appears to detect more scrapie in some countries. This is contrary to evidence suggesting the greater ability of the fallen stock survey to detect the disease. We applied meta-analysis techniques to study this apparent heterogeneity in the behaviour of the surveys across Europe. Furthermore, we conducted a meta-regression analysis to assess the effect of country-specific characteristics on the variability. We have chosen the odds ratios between the two surveys to inform the underlying relationship between them and to allow comparisons between the countries under the meta-regression framework. Baseline risks, those of the slaughtered populations across Europe, and country-specific covariates, available from the European Commission Report, were inputted in the model to explain the heterogeneity.ResultsOur results show the presence of significant heterogeneity in the odds ratios between countries and no reduction in the variability after adjustment for the different risks in the baseline populations. Three countries contributed the most to the overall heterogeneity: Germany, Ireland and The Netherlands. The inclusion of country-specific covariates did not, in general, reduce the variability except for one variable: the proportion of the total adult sheep population sampled as fallen stock by each country. A large residual heterogeneity remained in the model indicating the presence of substantial effect variability between countries.ConclusionThe meta-analysis approach was useful to assess the level of heterogeneity in the implementation of the surveys and to explore the reasons for the variation between countries.

A Bagging-Based Correction for the Mixture Model Estimator of Population Size

Estimation of a population size by means of capture-recapture techniques is an important problem occurring in many areas of life and social sciences. We consider the frequencies of frequencies situation, where a count variable is used to summarize how often a unit has been identified in the target population of interest. The distribution of this count variable is zero-truncated since zero identifications do not occur in the sample. As an application we consider the surveillance of scrapie in Great Britain. In this case study holdings with scrapie that are not identified (zero counts) do not enter the surveillance database. The count variable of interest is the number of scrapie cases per holding. For count distributions a common model is the Poisson distribution and, to adjust for potential heterogeneity, a discrete mixture of Poisson distributions is used. Mixtures of Poissons usually provide an excellent fit as will be demonstrated in the application of interest. However, as it has been recently demonstrated, mixtures also suffer under the so-called boundary problem, resulting in overestimation of population size. It is suggested here to select the mixture model on the basis of the Bayesian Information Criterion. This strategy is further refined by employing a bagging procedure leading to a series of estimates of population size. Using the median of this series, highly influential size estimates are avoided. In limited simulation studies it is shown that the procedure leads to estimates with remarkable small bias.

Prioritization of capacities for the elimination of dog-mediated human rabies in the Americas: building the framework

Abstract The region of the Americas pledged to eliminate dog-transmitted human rabies by 2015. After 30 years of sustained efforts, regional elimination appears possible as dog-mediated human rabies cases are at an all-time low, and a number of countries and territories have already eliminated the disease. In this setting, there is an opportunity to generate a framework to support countries strategies in the achievement and maintenance of rabies-free status (RFS). To this end, we describe the development of a multi-criteria decision analysis (MCDA) model to help the evaluation of rabies programmes and the identification of the best investment strategy for countries and territories to improve and efficiently maintain their rabies status. The model contemplates human and animal related capacities, six in each area, to comprehensively assess the wide scope of rabies programmes. An initial elicitation of expert opinion of values and weights for the MCDA model was performed via a web-based questionnaire. Even at this pilot stage, the model produces comparable capacity-scores, and overall (combined for public and animal health areas) as well as area-specific investment strategies. The model is being developed by the Pan American Health Organization (PAHO) as part of the regional efforts towards dog-mediated human rabies elimination and will be presented to the countries for review, refinement, contextualization, and testing. The aspiration is that countries use the model to identify the best allocation of resources towards the elimination of dog-mediated human rabies.

The evaluation of bias in scrapie surveillance: A review

Evaluation of surveillance systems is a common practice in the context of human health, but only recently has been applied in the veterinary field. Commonly, a series of attributes are monitored to assess the system. Suboptimal performance of the surveillance in relation to any of these attributes may lead to bias in the surveillance results. The intensity of scrapie surveillance has increased considerably in recent years as a result of public health concerns. In this paper, a number of approaches described in the literature for the evaluation of surveillance systems are reviewed, with a focus on the sensitivity and representativeness attributes of scrapie surveillance systems in the European Union. Many of the methods applied in other fields, such as ecology and public health, are exchangeable and relevant for scrapie surveillance.