Scrapie In Great Britain Research Articles

Will there be any more classical scrapie cases in sheep in Great Britain? A modelling study to predict future cases

The aim of this study was to apply a back-calculation model to Great Britain (GB) classical scrapie surveillance data, and use this model to estimate how many more cases might be expected, and over what time frame these cases might occur. A back-calculation model was applied to scrapie surveillance data between 2005 and 2019 to estimate the annual rate of decline of classical scrapie. This rate was then extrapolated to predict the number of future cases each year going forward. The model shows that there may be yet further cases of classical scrapie in GB. These will most likely occur in the fallen stock scheme, with approximately a 25% probability of at least 1 further scrapie positive, with a very low probability (~0.2%) of having up to three additional scrapie positives. This highlights the difficulty of completely eliminating all further cases, even in the presence of very effective control measures.

Evidence for more cost-effective surveillance options for bovine spongiform encephalopathy (BSE) and scrapie in Great Britain.

Transmissible spongiform encephalopathies (TSEs) are an important public health concern. Since the emergence of bovine spongiform encephalopathy (BSE) during the 1980s and its link with human Creutzfeldt–Jakob disease, active surveillance has been a key element of the European Union’s TSE control strategy. Success of this strategy means that now, very few cases are detected compared with the number of animals tested. Refining surveillance strategies would enable resources to be redirected towards other public health priorities. Cost-effectiveness analysis was performed on several alternative strategies involving reducing the number of animals tested for BSE and scrapie in Great Britain and, for scrapie, varying the ratio of sheep sampled in the abattoir to fallen stock (which died on the farm). The most cost-effective strategy modelled for BSE involved reducing the proportion of fallen stock tested from 100% to 75%, producing a cost saving of ca GBP 700,000 per annum. If 50% of fallen stock were tested, a saving of ca GBP 1.4 million per annum could be achieved. However, these reductions are predicted to increase the period before surveillance can detect an outbreak. For scrapie, reducing the proportion of abattoir samples was the most cost-effective strategy modelled, with limited impact on surveillance effectiveness.

Case-control study on the use of pituitary-derived hormones from sheep as a potential risk factor for the occurrence of atypical scrapie in Great Britain

A case-control study was conducted in 2013 to investigate the use of pituitary-derived hormones from sheep as a potential risk factor for the presence of atypical scrapie in Great Britain...

Epidemiological investigations on the potential transmissibility of a rare disease: the case of atypical scrapie in Great Britain.

Multiple cases of atypical scrapie in the same holding and co-existence with classical scrapie have been reported in Great Britain. A two-stage simulation tool was developed by combining a sampling algorithm and a hierarchical Bayesian model to simulate the number of positive cases of atypical scrapie from: (i) random sampling and (ii) using the actual sampled population in Great Britain, being the output probability of detection of flocks with one and more cases. Cluster analysis was conducted to assess the level of geographical over- and under-sampling over the years. The probability of detecting at least two cases of atypical scrapie in the same holding is much lower in simulated random data than in simulated actual data for all scenarios. Sampling bias in the selection of sheep for testing led to multiple sampling from fewer but larger holdings, Scotland, and areas of Wales were under-sampled and the South-West and East of England oversampled. The pattern of atypical scrapie cases observed is unlikely to be explained by a multi-case event epidemiologically linked. The co-existence of classical and atypical scrapie is a rare event with 19 holdings detected in GB and does not suggest an epidemiological link between the two types of disease.

The evolution of the prevalence of classical scrapie in sheep in Great Britain using surveillance data between 2005 and 2012

After the decline of the Bovine Spongiform Encephalopathy (BSE) epidemic in Great Britain (GB), scrapie remains the most prevalent animal Transmissible Spongiform Encephalopathy (TSE) present in GB. A number of control measures have been implemented for classical scrapie, and since 2005 there has been a large reduction in the number of observed cases. The objective of this study is to estimate two measures of disease frequency using up to date surveillance data collected during and after the implementation of different control measures established since 2004, and breeding for resistance schemes that ran from 2001 until 2009. This would enable an assessment of the effectiveness of both the breeding for resistance programme and the compulsory eradication measures in reducing the prevalence of scrapie in GB. Evaluation of the sensitivity of the rapid post-mortem test for scrapie indicated that it detected scrapie in the last 25% of the incubation period. A back-calculation model was developed to estimate the prevalence of infection at animal and flock-level. The results of the model indicated a mean drop of infection prevalence of 31% each year, leading to a 90% drop in infection prevalence between 2005, with an estimate of 5737 infected sheep in GB in 2012.The risks of classical scrapie infection in animals with genotypes of National Scrapie Plan Types I–IV (all other genotypes), relative to Type V (all genotypes containing V136 R154 Q171 and not A136 R154 R171), were estimated to be: 0, 0.0008, 0.07, and 0.21 respectively. The model estimated a very low rate of reporting of clinical suspects and a large decline from 2007 of the probability of a sheep being reported as a clinical suspect. The model also estimated that the expected number of sheep holdings with classical scrapie in 2012 was 215 (95% confidence interval: 33–437), out of a total of approximately 72,000 sheep holdings in GB. Model estimates indicate that the prevalence in 2012 has dropped to 10% of that in 2005, showing the effectiveness of the control measures. It also shows a bias in the destination of infected animals, with the majority of infected animals being detected in the fallen stock surveillance stream, and an extremely low proportion of animals detected as clinical suspects; this is very important in terms of the design of surveillance schemes for classical scrapie.

An economic evaluation of preclinical testing strategies compared to the compulsory scrapie flock scheme in the control of classical scrapie.

Cost-benefit is rarely combined with nonlinear dynamic models when evaluating control options for infectious diseases. The current strategy for scrapie in Great Britain requires that all genetically susceptible livestock in affected flocks be culled (Compulsory Scrapie Flock Scheme or CSFS). However, this results in the removal of many healthy sheep, and a recently developed pre-clinical test for scrapie now offers a strategy based on disease detection. We explore the flock level cost-effectiveness of scrapie control using a deterministic transmission model and industry estimates of costs associated with genotype testing, pre-clinical tests and the value of a sheep culled. Benefit was measured in terms of the reduction in the number of infected sheep sold on, compared to a baseline strategy of doing nothing, using Incremental Cost Effectiveness analysis to compare across strategies. As market data was not available for pre-clinical testing, a threshold analysis was used to set a unit-cost giving equal costs for CSFS and multiple pre-clinical testing (MT, one test each year for three consecutive years). Assuming a 40% within-flock proportion of susceptible genotypes and a test sensitivity of 90%, a single test (ST) was cheaper but less effective than either the CSFS or MT strategies (30 infected-sales-averted over the lifetime of the average epidemic). The MT strategy was slightly less effective than the CSFS and would be a dominated strategy unless preclinical testing was cheaper than the threshold price of £6.28, but may be appropriate for flocks with particularly valuable livestock. Though the ST is not currently recommended, the proportion of susceptible genotypes in the national flock is likely to continue to decrease; this may eventually make it a cost-effective alternative to the MT or CSFS.

Capture–Recapture Estimation by Means of Empirical Bayesian Smoothing with an Application to the Geographical Distribution of Hidden Scrapie in Great Britain

Summary The paper discusses population size estimation on the basis of a frequency distribution of zero-truncated counts and is motivated by a study on the geographical distribution of hidden scrapie in Great Britain. Aggregation of scrapie cases is considered at the county level and results in sparse zero-truncated count distributions which make the application of conventional capture–recapture procedures for estimating the hidden part of the scrapie-affected population difficult. We suggest a smoothed generalization of Zelterman’s estimator of population size which overcomes the overestimation bias of the conventional Zelterman estimator and instead produces a lower bound, which is typically larger than Chao’s lower bound estimator. The estimator uses an empirical Bayes approach with various choices for the prior distribution including a parametric choice of the gamma distribution as well as various non-parametric distributions. A simulation study investigates the performance of the new estimators, and also in comparison with conventional estimators. The empirical Bayes estimator with a non-parametric mixture model as prior performs well and the boundary problem of the conventional non-parametric discrete mixture model estimator leading to spurious population size is avoided. In the application to hidden scrapie in Great Britain the new estimators lead to maps of scrapie of observed–hidden ratios as well as completeness of the current surveillance system.

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 model's 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.

Spatial distribution of the active surveillance of sheep scrapie in Great Britain: an exploratory analysis

BackgroundThis paper explores the spatial distribution of sampling within the active surveillance of sheep scrapie in Great Britain. We investigated the geographic distribution of the birth holdings of sheep sampled for scrapie during 2002 – 2005, including samples taken in abattoir surveys (c. 83,100) and from sheep that died in the field ("fallen stock", c. 14,600). We mapped the birth holdings by county and calculated the sampling rate, defined as the proportion of the holdings in each county sampled by the surveys. The Moran index was used to estimate the global spatial autocorrelation across Great Britain. The contributions of each county to the global Moran index were analysed by a local indicator of spatial autocorrelation (LISA).ResultsThe sampling rate differed among counties in both surveys, which affected the distribution of detected cases of scrapie. Within each survey, the county sampling rates in different years were positively correlated during 2002–2005, with the abattoir survey being more strongly autocorrelated through time than the fallen stock survey. In the abattoir survey, spatial indices indicated that sampling rates in neighbouring counties tended to be similar, with few significant contrasts. Sampling rates were strongly correlated with sheep density, being highest in Wales, Southwest England and Northern England. This relationship with sheep density accounted for over 80% of the variation in sampling rate among counties. In the fallen stock survey, sampling rates in neighbouring counties tended to be different, with more statistically significant contrasts. The fallen stock survey also included a larger proportion of holdings providing many samples.ConclusionSampling will continue to be uneven unless action is taken to make it more uniform, if more uniform sampling becomes a target. Alternatively, analyses of scrapie occurrence in these datasets can take account of the distribution of sampling. Combining the surveys only partially reduces uneven sampling. Adjusting the distribution of sampling between abattoirs to reduce the bias in favour of regions with high sheep densities could probably achieve more even sampling. However, any adjustment of sampling should take account of the current understanding of the distribution of scrapie cases, which will be improved by further analysis of this dataset.

Prevalence of sheep infected with classical scrapie in Great Britain, 1993–2007

Extensive surveillance for classical scrapie has been carried out in Great Britain since 1993, the results of which can be used for monitoring the effect of control measures introduced since 2001. A back-calculation approach was used to estimate the prevalence of sheep infected with classical scrapie, which integrates data on reported clinical cases (1993-2007) and the results of fallen stock and abattoir surveys (2002-2007). The prevalence of classical scrapie in GB was fairly constant until 2003, although the estimates depended on assumptions made about the performance of diagnostic tests used in the surveys. If infected animals could be detected in the final quarter of the incubation period, the estimated prevalence was 0.6-0.7%, while if they could be detected in the final half of the incubation period, it was 0.3-0.4%. Between 2003 and 2007 the prevalence declined by around 40%, and the magnitude of the reduction was independent of assumptions made about the diagnostic tests.

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.

On the question of proportionality of the count of observed Scrapie cases and the size of holding

BackgroundThe present paper investigates the question of a suitable basic model for the number of scrapie cases in a holding and applications of this knowledge to the estimation of scrapie-affected holding population sizes and adequacy of control measures within holding. Is the number of scrapie cases proportional to the size of the holding in which case it should be incorporated into the parameter of the error distribution for the scrapie counts? Or, is there a different – potentially more complex – relationship between case count and holding size in which case the information about the size of the holding should be better incorporated as a covariate in the modeling?MethodsWe show that this question can be appropriately addressed via a simple zero-truncated Poisson model in which the hypothesis of proportionality enters as a special offset-model. Model comparisons can be achieved by means of likelihood ratio testing. The procedure is illustrated by means of surveillance data on classical scrapie in Great Britain. Furthermore, the model with the best fit is used to estimate the size of the scrapie-affected holding population in Great Britain by means of two capture-recapture estimators: the Poisson estimator and the generalized Zelterman estimator.ResultsNo evidence could be found for the hypothesis of proportionality. In fact, there is some evidence that this relationship follows a curved line which increases for small holdings up to a maximum after which it declines again. Furthermore, it is pointed out how crucial the correct model choice is when applied to capture-recapture estimation on the basis of zero-truncated Poisson models as well as on the basis of the generalized Zelterman estimator. Estimators based on the proportionality model return very different and unreasonable estimates for the population sizes.ConclusionOur results stress the importance of an adequate modelling approach to the association between holding size and the number of cases of classical scrapie within holding. Reporting artefacts and speculative biological effects are hypothesized as the underlying causes of the observed curved relationship. The lack of adjustment for these artefacts might well render ineffective the current strategies for the control of the disease.

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.

Control of classical scrapie in Great Britain

CLASSICAL scrapie has been recognised as a fatal neurological disease in sheep in Great Britain for almost 300 years and, until recently, control at flock level has been difficult to...

Application of one-list capture–recapture models to scrapie surveillance data in Great Britain

In this paper, we apply one-list capture–recapture models to estimate the number of scrapie-affected holdings in Great Britain. We applied this technique to the Compulsory Scrapie Flocks Scheme dataset where cases from all the surveillance sources monitoring the presence of scrapie in Great Britain, the abattoir survey, the fallen stock survey and the statutory reporting of clinical cases, are gathered. Consequently, the estimates of prevalence obtained from this scheme should be comprehensive and cover all the different presentations of the disease captured individually by the surveillance sources. Two estimators were applied under the one-list approach: the Zelterman estimator and Chao's lower bound estimator. Our results could only inform with confidence the scrapie-affected holding population with clinical disease; this moved around the figure of 350 holdings in Great Britain for the period under study, April 2005–April 2006. Our models allowed the stratification by surveillance source and the input of covariate information, holding size and country of origin. None of the covariates appear to inform the model significantly.

Prevalence of sheep infected with classical scrapie in Great Britain: integrating multiple sources of surveillance data for 2002

Estimates for the prevalence of sheep infected with classical scrapie are essential for assessing the efficacy of control strategies that have been implemented in Great Britain (GB). Here a back-calculation approach was used to estimate the prevalence in the GB national flock by integrating data on reported cases and the results of abattoir and fallen stock surveys for 2002. Prevalence estimates ranged from 0.33 to 2.06%, depending on the estimates used for the frequencies of prion protein (PrP) genotypes in the national flock and the stage of incubation at which the diagnostic tests used are able to detect infected animals. The risk of infection was found to be higher than that of clinical disease, especially in those PrP genotypes that have a later age at onset of clinical disease. Moreover, results suggest that a high proportion (more than 55%) of infected animals surviving to disease onset die on farm before clinical signs become apparent, which helps account for the high observed prevalence in the fallen stock compared with the abattoir survey. The analyses indicated that attention needs to be given to identifying the stage of incubation at which diagnostic tests are able to detect infected animals and obtaining better demographic data for the GB national flock.

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.

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.

Analysis of data from the passive surveillance of scrapie in Great Britain between 1993 and 2002

Reports of clinical scrapie in Great Britain between January 1, 1993 and December 31, 2002 were reviewed. Scrapie was confirmed in 4142 sheep on 1099 holdings. The cumulative case and...

Flock-level risk factors for scrapie in Great Britain: analysis of a 2002 anonymous postal survey

BackgroundIn November 2002, an anonymous postal survey of sheep farmers in Great Britain (GB) was conducted to identify factors associated with the flock-level occurrence of scrapie. This survey was undertaken to update an earlier postal survey in 1998, and was the first occasion in which a large-scale postal survey had been repeated.ResultsThe results of the 2002 survey indicated that scrapie was more likely to occur in certain geographic regions; in purebred compared to commercial flocks; in larger flocks; in flocks which lambed in group pens compared to those which lambed in individual pens; in flocks which always lambed in the same location compared to those which did not; and in farms which kept certain breeds of sheep. In addition to these factors, the likelihood of the disease occurring in homebred animals was higher in flocks which bred a greater proportion of replacement animals or which bought-in lambs. Finally, within-flock transmission following exposure was more likely to occur in hill flocks compared to other farm types; in flocks which bred a greater proportion of replacement animals; and in farms which kept a certain crossbreed of ewe.ConclusionThe risk factors identified from the 1998 and 2002 anonymous postal surveys in Great Britain were similar. However, differences between the surveys were identified in the influence of region and of purchasing behaviour on the risk of scrapie. These differences are most likely a consequence of changes in farmer awareness and the impact of the 2001 foot-and-mouth disease epidemic, respectively.