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1.  Spatial distribution of the active surveillance of sheep scrapie in Great Britain: an exploratory analysis 
Background
This 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).
Results
The 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.
Conclusion
Sampling 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.
doi:10.1186/1746-6148-5-23
PMCID: PMC2720384  PMID: 19607705
2.  On the question of proportionality of the count of observed Scrapie cases and the size of holding 
Background
The 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?
Methods
We 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.
Results
No 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.
Conclusion
Our 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.
doi:10.1186/1746-6148-5-17
PMCID: PMC2697145  PMID: 19419538
3.  Explaining the heterogeneous scrapie surveillance figures across Europe: a meta-regression approach 
Background
Two 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.
Results
Our 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.
Conclusion
The 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.
doi:10.1186/1746-6148-3-13
PMCID: PMC1924846  PMID: 17598881

Results 1-3 (3)