A "shotgun" method for tracing the birth locations of sheep from flock tags, applied to scrapie surveillance in Great Britain.

Movement records are often used to identify animal sample provenance by retracing the movements of individuals. Here we present an alternative method, which uses the same identity tags and movement records as are used to retrace movements, but ignores individual movement paths. The first step uses a simple query to identify the most likely birth holding for every identity tag included in a database recording departures from agricultural holdings. The second step rejects a proportion of the birth holding locations to leave a list of birth holding locations that are relatively reliable. The method was used to trace the birth locations of sheep sampled for scrapie in abattoirs, or on farm as fallen stock. Over 82% of the sheep sampled in the fallen stock survey died at the holding of birth. This lack of movement may be an important constraint on scrapie transmission. These static sheep provided relatively reliable birth locations, which were used to define criteria for selecting reliable traces. The criteria rejected 16.8% of fallen stock traces and 11.9% of abattoir survey traces. Two tests provided estimates that selection reduced error in fallen stock traces from 11.3% to 3.2%, and in abattoir survey traces from 8.1% to 1.8%. This method generated 14,591 accepted traces of fallen stock from samples taken during 2002-2005 and 83,136 accepted traces from abattoir samples. The absence or ambiguity of flock tag records at the time of slaughter prevented the tracing of 16-24% of abattoir samples during 2002-2004, although flock tag records improved in 2005. The use of internal scoring to generate and evaluate results from the database query, and the confirmation of results by comparison with other database fields, are analogous to methods used in web search engines. Such methods may have wide application in tracing samples and in adding value to biological datasets.

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.