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

Abstract

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.

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

“…The model is described in full as supplementary material (Appendix A). The model is similar in principle to a previous approach (Gubbins, 2008), except that (i) it estimates prevalence over several years data, (ii) it allows the rate of under-reporting of clinical suspects to vary over time, and (iii) it assumes that animals show overt clinical signs at clinical onset, whereas in (Gubbins, 2008) it is allowed for a large proportion of animals to die at clinical onset prior to overt clinical signs.…”

“…Relative risk of infection The model is similar in principle to that of a previous back-calculation model to estimate scrapie prevalence from multiple data streams in GB (Gubbins, 2008). One important difference is the estimation of the differential slaughter risk (K).…”

“…Gubbins, 2008), and the lognormal distribution has also been found to be a good fit to incubation periods for other TSEs such as BSE (Wells et al, 2007). For NSP groups I-IV, the incubation period distribution was estimated separately for each by fitting a lognormal incubation period to the observed age at onset of clinical cases in the Scrapie Notifications Database (SND), accounting for the age distribution of the population (from Gubbins et al, 2003) (see Appendix B).…”

“…The number of infected sheep in each genotype group was estimated according to the method used in a previous study (Gubbins, 2008) (see Appendix A).…”

“…Previous attempts to estimate disease frequency at animal and flock-levels used data generated by surveillance before the eradication measures and the breeding for resistance programmes could have had any impact on the disease frequency. A prevalence estimate ranging from 0.33 to 2.06% using abattoir and fallen stock survey data for 2002 was obtained (Gubbins, 2008). A backcalculation approach was used to estimate the prevalence of sheep infected with classical scrapie, integrating data on reported clinical cases (1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007) and the results of fallen stock and abattoir surveys (2002)(2003)(2004)(2005)(2006)(2007) .…”