Spatial analysis of bovine spongiform encephalopathy in Galicia, Spain (2000–2005

Spatial analysis of bovine spongiform

encephalopathy in Galicia, Spain (2000–2005)

A. Allepuz a,*, A. Lopez-Quılez b, A. Forte b,G. Fernandez c, J. Casal a

a Centre de Recerca en Sanitat Animal (CReSA)/Departament de Sanitat i Anatomia Animals,

Edifici V, Facultat de Veterinaria, Universitat Autonoma de Barcelona,

08193 Bellaterra, Barcelona, Spainb Grup d’Estadıstica espacial i temporal en Epidemiologia i medi ambient (GEeit�E�ma)/

Departament d’Estadıstica i Investigacio Operativa, Universitat de Valencia, Burjassot, Spainc Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad de Santiago

de Compostela, Lugo, Spain

Received 16 May 2006; received in revised form 10 November 2006; accepted 28 November 2006

Abstract

In Spain, the first bovine spongiform encephalopathy (BSE) case was detected in 2000 in a cow

born in the Galicia region (Northwestern Spain). From then and until October 2005, 590 cases were

detected, 223 of them in Galicia.

In 1994, meat and bone meal (MBM) was banned on ruminant feed and, in 1996, an EU decision

mandating an overall change in MBM processing was implemented. This decision was gradually

applied in the territory and not enforced before July 1998. The objective of this study was to explore

clustering of BSE cases and estimate the standard incidence ratio (SIR) of BSE in Galicia. Our study

was based on the BSE cases detected during the surveillance period 2000–2005 in the Galicia region.

These cases were divided, based on birth date, into two periods: animals born from 1994 to July

1998, and those born after July 1998. We tested the role of cross-contamination on the geographical

SIR distribution for both periods. Hierarchical Bayesian models were used to model the over-

dispersion and lack of independence of the SIR estimates. The geographical distribution of the

standard incidence ratio of BSE between both periods was different. In the second period, the SIR

was reduced in some areas. The reduction in these areas could be attributable to the changes in the

www.elsevier.com/locate/prevetmed

Preventive Veterinary Medicine 79 (2007) 174–185

* Corresponding author. Present address: Unit of Veterinary Epidemiology, Centre de Recerca en Sanitat Animal

(CReSA), Campus UAB, Edifici CReSA, 08193 Bellaterra, Barcelona, Spain. Tel.: +34 93 581 4557;

fax: +34 93 581 44 90.

E-mail address: [email protected] (A. Allepuz).

0167-5877/$ – see front matter # 2006 Elsevier B.V. All rights reserved.

doi:10.1016/j.prevetmed.2006.11.012

processing of MBM. We did not find any statistical link between the poultry population and the

standard incidence ratio, but pig population had a positive effect.

# 2006 Elsevier B.V. All rights reserved.

Keywords: Bovine spongiform encephalopathy; Spatial analysis; Bayesian model; Cross-contamination

1. Introduction

Bovine spongiform encephalopathy (BSE) is a progressive neurological disorder of

cattle. It was first diagnosed in United Kingdom in 1986 (Wells et al., 1987). Different

studies suggest that the disease was originated from feed containing meat and bone meal

(MBM), contaminated by a scrapie-like agent derived from sheep or cattle (Willesmith

et al., 1988; Anderson et al., 1996). Based on these results, MBM was banned in ruminant

feed in Europe in 1994 (Decision 94/381).

Despite this ban, many cases of BSE appeared in animals born after 1994. Cross-

contamination between feedstuff for ruminants and other species has been suggested as a

hypothesis to explain the cases of animals born after MBM ban (Hoinville, 1994; Denny

and Hueston, 1997). The implementation of the July 1996 EU-Decision, mandating an

overall change in the rendering system to 133 8C, 3 bars and 20 min, was progressively

ensured during 1997 and 1998. For this study we have considered that the rendering system

was ineffective for inactivating the BSE agent until July 1998. Improperly processed MBM

was produced and sold to the feed industry until mid-1998. Therefore, until July 1998,

cattle feed could have been contaminated with low levels of MBM (Anon.; http://

europa.eu.int/comm/food/fs/sc/ssc/out126_en.pdf). In 2001, MBM were banned for all

domestic species (2000/766/CE).

The aim of this work is to explore BSE clustering, study the spatial distribution of the

standard incidence ratio (SIR) of BSE in the Galicia region (Northwestern Spain) and test

the role of cross-contamination in its geographical distribution.

2. Material and methods

2.1. Area under study

The study was conducted in the autonomous community of Galicia, which is in the

northwest of Spain, north of Portugal. It has an area of 295.75 km2 and is divided in 4

provinces and 314 municipalities.

In this region, the cattle population is 1,128,500 animals; 693,800 of them are cattle

aged more than 15 months (population at risk) and 444,000 dairy animals.

Lugo and Coruna provinces, with 290,658 and 283,550 head of cattle, respectively, are

the ones with highest cattle population in the Galicia region. In Coruna province the dairy

population represents 72% of the total cattle population, 204,084 out of a total of 283,550.

In Lugo province there is not such a big difference between beef and dairy population;

there are 171,658 dairy animals out of a total population of 290,658 animals.

A. Allepuz et al. / Preventive Veterinary Medicine 79 (2007) 174–185 175

2.2. Data

Date and place of birth and date of detection of BSE cases were obtained from the

Galician government. Our study was based on cases detected by the surveillance system

from 2000 to June 2005. During this period, the detection of BSE cases was based on the

Mandatory Reporting System of clinical suspicions and the active surveillance programme

based on rapid tests carried out on every cow aged over 24 months. Because most of the

infections occur during calfhood (Willesmith et al., 1988) the period of infection for the

BSE cases was established as the year of birth, and they were located at the farm where the

animals were born. We included in the analysis BSE cases diagnosed in cattle born in

Galicia after 1994, and we divided them in two periods; between 1994 and July 1998 and

after July 1998. In the first period, cross-contamination is believed to have happened

because improperly processed MBM was produced and sold to the feed industry. In the

second period, after July 1998, when the change in MBM processing was made effective,

cross-contamination is not believed to have happened.

Data of the population at risk (cattle over 15 months), pig and poultry population were

obtained at municipality level from 1999 agricultural census published by Galicia

autonomous government. Taking into account that BSE incidence varies according to the

production type (Willesmith et al., 1988; Ducrot et al., 2003), the cattle population was

divided into dairy and beef cattle.

2.3. Cluster analysis

To explore the spatial distribution of the BSE cases we used SatScan1 v5.1 (http://

www.satscan.org) described by Kulldorff (1997). Geographical coordinates for most of

the farms were unknown. All the cases were located at the centroid of the municipality,

the smallest administrative unit, where the animal was born. The aggregation level

of the analysis was the municipality. We assumed that, under the null hypothesis,

the number of cases followed a Poisson distribution and we ran a purely spatial

analysis.

The spatial scan statistic can locate the site and test the significance of specific clusters.

It searches for clusters by using a variable circular window size to detect spatial clusters in

large areas, while controlling for the underlying population (Kulldorff, 1997). The circle is

centred on each of the points. For each point, the size of the circle varies continuously from

zero to some upper limit specified by the user (20% population at risk in our case). For each

location and size of the scanning window, the alternative hypothesis is that there is a higher

rate within the circle than outside. If a cluster is identified, the statistical significance is

obtained by Monte Carlo hypothesis testing (Kulldorf, 2003). We run two purely spatial

analyses for each period (animals born between 1994 and July 1998 and after July 1998)

one with the dairy and the other with the beef population.

2.4. Disease mapping

The aggregation level used in the analysis was the municipality (i = 1, . . ., 314). For

each municipality we estimated the standardised incidence ratio (SIRi), which represents

A. Allepuz et al. / Preventive Veterinary Medicine 79 (2007) 174–185176

an increase/decrease in the risk of infection compared to a standard risk evaluated in the

whole Galicia region:

SIRi ¼Oi

Ei

being Oi and Ei the observed and expected BSE cases, respectively, in each municipality.

As the incidence varies according to the production type we differentiated the cases in

each municipality by breed. The expected cases in each municipality were estimated by

applying the overall BSE ratio in the whole of Galicia to the cattle population in each

municipality.

Ei ¼ Rdairy� Dairyi þ Rbeef � Beefi

Being ‘‘Rdairy’’ and ‘‘Rbeef’’ the overall BSE ratio in dairy and beef, respectively, while

Dairyi and Beefi are the dairy and beef populations in each municipality.

For an uncommon disease, a map of standardised rates suffers because the rates are

over-dispersed. Their variability only partly reflects genuine geographical heterogeneity,

the remaining variance being due to Poisson variability. The most extreme rates tend to

occur in the areas with the smallest populations. On the other hand, geographically close

areas tend to have similar disease rates (Clayton and Bernardinelli, 1992) so independence

of risk between close areas cannot be assumed. To model the over-dispersion of the

parameter of interest (SIRi) and take into account the risk dependence between close areas,

spatial hierarchical Bayesian models were used.

To implement the model we used WinBUGS, Software Version 1.4.1 (http://www.mrc-

bsu.cam.ac.uk/ bugs), Windows version, for Bayesian analysis using Gibbs sampling

(Lawson et al., 2003).

2.5. Construction of the Bayesian model

As BSE is a non-contagious and rare disease, we assume it occurs independently in

individuals with equal probability and that the observed number of BSE cases (Oi) in each

of the 314 municipalities can be modelled as a Poisson distribution centred on m.

miðmi ¼ SIRiEiÞ:

Oi� PoissonðmiÞTo take into account the lack of independence of the risk between contiguous

municipalities, a random component (bi) with spatial structure can be used. This

component is based on a matrix of contiguities between geographical units. This spatial

component takes into account the spatial dependence between adjacent municipalities. The

prior distribution of this parameter follows a normal distribution:

bi�Nð]i; tniÞwhere \i is the mean of the spatial component in the set of municipalities adjacent to

municipality i (neighbours) and t is the precision, inverse of variance, weighted by ni, the

number of neighbours of municipality i.

A. Allepuz et al. / Preventive Veterinary Medicine 79 (2007) 174–185 177

To model the over-dispersion of the parameter of interest, the model also included a

random component (ai) without spatial structure. For the prior distribution of ai we chose a

normal distribution centred on zero:

ai�Nð0; nÞwhere n is the precision of the prior distribution. In order to test the hypothesis of cross-

contamination between cattle feedstuff and feedstuff for other species (pigs and

poultry) we added the population of these species as covariates in the model. Both

effects and the two covariates were linearly added to the prior distribution of the

logarithm of SIRi:

log SIRi ¼ b0 þ b1pigi þ b2poultryi þ ai þ bi

To compare the adjustment of the different models we used the deviance information

criterion (DIC). DIC is a measure of model fit penalised by the complexity of the model and

its value is calculated by adding the effective number of parameters to the posterior mean

deviance of the model.

The ‘‘best fit’’ model is the one with the smallest DIC value (Abrial et al., 2003). In

order to fully manage the statistical modelling prior distributions were established for

the parameters. Non-informative prior knowledge was considered with normal

distributions of mean 0 and variance 10,000 for both covariate parameters and gamma

distributions of mean 1 and variance 10 for t and n, the precision parameters of the two

random effects. The elicitation of hyperprior distributions in this type of models is a very

challenging issue in Bayesian statistics that is generating very fruitful discussions and

results (Gelman, 2006). In this scenario, Gamma models for precision parameters have

been the most popular proposal because of conditional conjugancy. We have been careful

with these prior distributions and we have not worked with extremely small

hyperparameter values.

The posterior distribution of the parameters was obtained from 25,000 Markov chain

Monte Carlo simulations (MCMC) after a burn-in of 5000 simulations. Conformity

analysis was made from the percentile posterior distribution given by the quantiles of the

usable chain, making appropriate interpretations in the context of disease mapping

(Richardson et al., 2004).

3. Results

3.1. Descriptive analysis

In Spain, the first BSE case was detected in 2000 in Galicia (Northwestern Spain). In

Galicia, 223 BSE cases have been confirmed, representing 36.5% of all the BSE cases

detected in Spain until October 2005. In Table 1, a descriptive analysis of the BSE cases

detected in Galicia is given. The incidence in the dairy and beef populations was different,

3.65 and 2.5 cases per 10,000 cattle in the dairy and beef cattle populations, respectively.

Of the 223 cases detected in the surveillance period 2000–2005, 11 cases were born before

the ban on meat and bone meal in cattle feed, 164 of them were born between the ban and

A. Allepuz et al. / Preventive Veterinary Medicine 79 (2007) 174–185178

A. Allepuz et al. / Preventive Veterinary Medicine 79 (2007) 174–185 179

Table 1

Frequency of BSE cases stratified by province, year of detection, age of animals and animal type (beef, dairy)

Region Age Year of detection Cases

Beef Dairy 2000 2001 2002 2003 2004 2005 Beef Dairy

Mean Min–Max Mean Min–Max

Lugo 7.0 5–10 6.2 4–11 1 14 7 26 24 16 55 33

Coruna 6.4 5–9 6.5 4–11 1 7 10 17 13 14 52 10

Pontevedra 6.7 5–9 6.2 4–9 0 2 14 18 15 11 47 13

Orense 6.6 5–9 6.7 5–9 0 3 3 1 5 1 4 9

Total 6.67 5–9.25 6.4 4.2–10 2 26 34 62 57 42 158 65

Fig. 1. Distribution by semesters of BSE cases of animals born in Galicia until October 2005 by birth cohort (total

223 cases). (a) Ban on MBM for ruminant feed. (b) Effective implementation of rendering system to inactivate the

BSE agent (July 1998).

Fig. 2. Representation of the location and size of the cluster of BSE cases in dairy (a) and beef (b) cattle between

1994 and July 1998 (circles) on a choroplethmap of the dairy and beef cattle population (municipalities with

higher populations are those with higher colour intensity). (a) Dairy cattle: observed, 43; expected, 17 ( p-

value = 0.001). (b) Beef cattle: observed, 15; expected, 3 ( p-value = 0.002).

July 1998, when the rendering system was ineffective to inactivate the BSE agent, and 49

cases were born after July 1998 (Fig. 1).

3.2. Cluster analysis

In the first period, between 1994 and July 1998, the SatScan detected significant clusters

in the dairy and beef cattle populations. The size of the clusters is quite different but they

are both located in the central part of the area under study. In Fig. 2, the location and size of

clusters are represented with a choropleth map of the beef and dairy populations. In the

second period, after July 1998, the SatScan did not detect any statistically significant

cluster.

3.3. Disease mapping

The spatial hierarchical Bayesian model with both random effects suggested that the

risk of BSE infection over Galicia was not homogeneous in both periods. In the first period,

from 1994 to July 1998, municipalities located in the central and southeastern areas were

exposed to a risk of infection between 2 and 4 times higher than in the rest of the territory.

In the second period, after July 1998, the higher-risk municipalities were located, mainly in

the northwestern part of the region (Fig. 3). We calculated the DIC value of the different

combinations of the model with the covariates. In both periods, the smallest DIC value was

the one with the two random components and the pig population as covariate. There is a

90% probability that there is a positive relationship between the BSE risk and the pig

population for both periods. In the first period (animals born between 1994 and July 1998)

the regression coefficient of the pig population was centred on 0.2083 (�0.03, 0.45). This

means an increase of between 0.97 and 1.57 times in the BSE risk for 10,000 pigs in each

municipality. In the second period, animals born after July 1998, the BSE risk was

increased by between 0.96 and 1.77 times, a mean value of 1.304 for 10,000 pigs in each

municipality (Tables 2 and 3).

A. Allepuz et al. / Preventive Veterinary Medicine 79 (2007) 174–185180

Fig. 3. Geographical distribution of the standardised incidence ratio of BSE for both periods (SIR values are

multiplied by 100). (a) 1994–July 1998. (b) After July 1998.

A.

Allep

uz

eta

l./Preven

tiveV

eterina

ryM

edicin

e7

9(2

00

7)

17

4–

18

51

81

Table 2

Estimate of the parameters of the different combination of the models for period 1, when the rendering system was ineffective for inactivating the BSE agent (1994–July

1998)

Model Model (log mi) Estimate MC error Percentile distribution DIC

5% 10% 50% 90% 95%

Two random components,

pigs and poultry as covariates

log Ei + ai + bi + b0 + b1pigi +

b2poultryi

b0: �0.409 0.005 �0.73 �0.64 �0.39 �0.16 �0.1 398.774

b1: 0.306 0.003 0.03 0.09 0.29 0.5 0.56

b2: �0.904 0.008 �2.1 �1.81 �0.86 0.01 0.23

Two random components,

pigs as covariate

log Ei + ai + bi + b0 + b1pigi b0: �0.464 0.006 �0.79 �0.71 �0.45 �0.22 �0.16 397.447

b1: 0.208 0.004 �0.03 0.01 0.2 0.39 0.45

Two random components,

poultry as covariate

log Ei + ai + b0 + b1pigi b0: �0.326 0.007 �0.64 �0.56 �0.32 �0.1 �0.04 399.537

b1: �0.338 0.012 �1.32 �1.08 �0.32 0.39 0.6

Without spatial component,

pigs as covariate

log Ei + ai + b0 + b1pigi b0:�0.502 0.004 �0.78 �0.71 �0.49 �0.3 �0.25 397.705

b1: 0.330 0.002 0.11 0.16 0.33 0.5 0.56

DIC: Deviance information criterion.

A.

Allep

uz

eta

l./Preven

tiveV

eterina

ryM

edicin

e7

9(2

00

7)

17

4–

18

51

82

Table 3

Estimate of the parameters of the different combination of the models for period 2, when the rendering system was effective for inactivating the BSE agent (after July 1998)

Model Model (log mi) Estimate MC error Percentile distribution DIC

5% 10% 50% 90% 95%

Two random components,

pigs and poultry as covariates

log Ei + ai + bi + b0 + b1pigi +

b2poultryi

b0: �0.512 0.01 �1.5 �0.91 �0.48 �0.14 �0.05 189.474

b1: 0.319 0.003 �0.04 0.03 0.31 0.6 0.7

b2: �0.48 0.016 �2.42 �1.89 �0.39 0.79 1.1

Two random components,

pigs as covariate

log Ei + ai + bi + b0 + b1pigi b0: �0.536 0.01 �1.08 �0.94 �0.5 �0.16 �0.08 188.470

b1: 0.266 0.002 �0.04 0.02 0.26 0.5 0.57

Two random components,

poultry as covariate

log Ei + ai + b0 + b1pigi b0: �0.386 0.01 �0.89 �0.75 �0.36 �0.03 0.03 190.05

b1: 0.28 0.008 �1.02 �0.7 0.31 1.22 1.48

Without spatial component,

pigs as covariate

log Ei + ai + b0 + b1pigi b0: �0.473 0.009 �0.96 �0.84 �0.44 �0.14 �0.06 191.274

b1: 0.263 0.002 �0.02 0.04 0.26 0.48 0.54

DIC: Deviance information criterion.

4. Discussion

Several studies have been carried out in order to study the spatial distribution of BSE

(Doherr et al., 2002; Stevenson et al., 2000, 2005; Abrial et al., 2003, 2005a) in all of them

the geographical distribution of the disease has been not homogeneous and clusters have

been detected in specific locations.

In France, Abrial et al. (2003, 2005a) concluded that the risk of infection with the BSE

agent in Western France and in the whole French territory was not randomly distributed

after the ban of meat and bone meal in cattle feed. Poultry density did not significantly

influence the risk of BSE, whereas the pig density was significantly associated with an

increase in the risk of 2.4% per 10,000 pigs (Abrial et al., 2005b).

In Great Britain, Stevenson et al. (2005) observed that after the feed ban there were

spatially aggregated areas of unexplained risk in the northern and eastern regions of Great

Britain. Area-level BSE risk was additionally associated with greater number of pigs per

area, relative to cattle. In Switzerland, the clusters were located in regions with a high pig

density, but there were other regions with higher pig and poultry densities that had no

clusters (Doherr et al., 2002).

In Spain, MBM was banned for ruminant feeding in 1994, but not until 2001 in other

species. The July 1996 EU-Decision, mandating an overall change in the rendering system,

was applied gradually over the country and until July 1998 the rendering system was not

considered effective to inactivate the BSE agent. The distribution of BSE cases by birth

year (Fig. 1) suggested that after mid-1998 the number of BSE cases began to decrease.

This distribution could indicate that the change on the rendering system of meat and bone

meal from mammalian animals for animal feed was an effective measure, reducing the risk

of cross-contamination and therefore the number of cases. This is supported by the change

in the spatial distribution of the standardised incidence ratio of BSE between both periods.

In the first period, there are some areas in the central and southeastern part where the SIR

value has been between 2 and 4 times higher than in other areas. In the second period some

of these areas present a value near to 1, indicating a reduction of the risk which could be

attributable to the changes in the processing of MBM (Fig. 3).

Despite the reduction of risk in the second period, the model suggested a positive

relationship between pig population and BSE risk for both of them. The influence of pig

population on the standard incidence ratio in the first period, when rendering system was

not effective, and the second period was not different. The gradual application over the

region of the change in feed processing could partly explain the fact that pig population had

a positive effect on BSE risk in the second period. On the other hand, local delivery of feed

has been assumed in this study and this is a practice that could always not been carried out.

Big feed companies may supply feed to farms situated in distant municipalities.

In our study, we did not find a statistical link with poultry population. This could be

explained by the high level of autonomy in the poultry industry. In many cases, the same

company is the owner of the farm and the feed processing plant, so it is not common to find

feed processing plants delivering feed for poultry and other species.

Finally, there could be other factors influencing the spatial distribution of the SIR of BSE.

Regional differences in the processing and use of MBM by rendering plants could make

regional differences in the transmission and amplification mechanisms of the infective agent

A. Allepuz et al. / Preventive Veterinary Medicine 79 (2007) 174–185 183

(Stevenson et al., 2005). Different rates of cross-contamination with contaminated MBM

between areas (Sheridan et al., 2005), the heterogeneity in the level of vigilance between

regions (Cuenot et al., 2003), regional differences in the levels of compliance with the feed

ban and the identification and reporting of cases between areas (Doherr et al., 2002), or

different risk factors characterising the feedstuff factories and the potential for cross-

contamination on farms or at the factories, might produce different BSE risks (Abrial et al.,

2005a). However, it is not easy to have reliable information associated with all these factors,

and because of that it was not possible to include them in the statistical analysis.

5. Conclusion

The spatial distribution of the risk of infection with the BSE agent is not homogeneous

in both periods under study. In the first period, there are some areas in the central and

southeastern part of Galicia where the risk of infection has been between 2 and 4 times

higher than in other areas. In the second period, these areas show a standard incidence ratio

near to 1, indicating a reduction of the risk. This reduction could be attributable to the

changes in the processing of MBM in the region.

References

Abrial, D., Calavas, D., Lauvergne, N., Morignat, E., Ducrot, C., 2003. Descriptive spatial analysis of BSE in

western France. Vet. Res. 34, 749–760.

Abrial, D., Calavas, D., Jarrige, N., Ducrot, C., 2005a. Spatial heterogeneity of the risk of BSE in France following

the ban of meat and bone meal in cattle feed. Prev. Vet. Med. 67, 69–82.

Abrial, D., Calavas, D., Jarrige, N., Ducrot, C., 2005b. Poultry, pig and the risk of BSE following the feed ban in

France—a spatial analysis. Vet. Res. 36, 615–628.

Anderson, R.M., Donelly, C.A., Ferguson, N.M., Woolhouse, M.E.J., Watt, C.J., Udy, H.J., MaWhinney, S.,

Dunstan, S.P., Southwood, T.R.E., Wilesmith, J.W., Ryan, J.B.M., Hoinville, L.J., Hillerton, J.E., Austin, A.R.,

Wells, G.A.H., 1996. Transmission dynamics and epidemiology of BSE in British cattle. Nature 382, 779–787.

Anon., 4/12/2000. European Decision 2000/766/EC.

Anon., 8/7/1996. European Decision 1996/449/EC.

Anon., 27/6/94. European Commission Decision 1994/381/EC.

Anon., 2000. Report on the Assessment of the Geographical BSE Risk of Spain (http://europa.eu.int/comm/food/

fs/sc/ssc/out126_en.pdf).

Clayton, D.G., Bernardinelli, L., 1992. Bayesian methods for mapping disease risk. In: Elliott, P., Cuzick, J.,

English, D., Stern, R. (Eds.), Geographical and Environmental Epidemiology: Methods for Small-Area

Studies. Oxford University Press, Oxford, pp. 205–220.

Cuenot, M., Calavas, D., Abrial, D., Gasqui, P., Cazeau, G., Ducrot, C., 2003. Temporal and spatial patterns of the

clinical surveillance of BSE in France, analysed from January 1991 to May 2002 through a vigilance index.

Vet. Res. 34, 261–272.

Denny, G.O., Hueston, W.D., 1997. Epidemiology of bovine spongiform encephalopathy in Northern Ireland 1988

to 1995. Vet. Rec. 140, 302–306.

Doherr, M.G., Hett, A.R., Rufenacht, J., Zurbrigen, A., Heim, D., 2002. Geographical clustering of cases of bovine

spongiform encephalopathy (BSE) born in Switzerland after the feed ban. Vet. Rec. 151, 467–472.

Ducrot, C., Roy, P., Morignat, E., Baron, T., Calavas, D., 2003. How the surveillance system may bias the results of

analytical epidemiological studies on BSE: prevalence among dairy versus beef suckler cattle breeds in

France. Vet. Res. 34, 185–192.

A. Allepuz et al. / Preventive Veterinary Medicine 79 (2007) 174–185184

Gelman, A., 2006. Prior distributions for variance parameters in hierarchical models. Bayesian Anal. 1, 515–534

(comment on article by Browne and Draper).

Hoinville, L.J., 1994. Decline in the incidence of BSE in cattle born after the introduction of the feed ban. Vet. Rec.

134, 274–275.

Kulldorff, M., 1997. A spatial scan statistic. Commun. Stat. Theor. M 26, 1481–1496.

Kulldorf M., 2003. SatScan User Guide for Version 4.0.3. http://www.satscan.org.

Lawson, A.B., Browne, W.J., Vidal Rodeiro, C.L., 2003. Disease mapping with WinBUGS and MLwiN. Wiley,

Chichester.

Richardson, S., Thomson, A., Best, N.G., Elliott, P., 2004. Interpreting posterior relative risk estimates in disease

mapping studies. Environ. Health Perspect. 112, 1016–1025.

Sheridan, H.A., MacGrath, G., Fallon, R., Shoukri, M.S., Martin, S.W., 2005. A temporal-spatial analysis of

bovine spongiform encephalopathy in Irish cattle herds, from 1996 to 2000. Can. J. Vet. Res. 69, 19–25.

Stevenson, M.A., Wilesmith, J.W., Ryan, J.B.M., Morris, R.S., Lawson, A.B., Pfeiffer, D.U., Lin, D., 2000.

Descriptive spatial analysis of the epidemic of bovine spongiform encephalopathy in Great Britain to June

1997. Vet. Rec. 147, 371–384.

Stevenson, M.A., Morris, R.S., Lawson, A.B., Wilesmith, J.W., Ryan, J.B.M., Jackson, R., 2005. Area-level risks

for BSE in British cattle before and after July 1988 meat and bone meal feed ban. Prev. Vet. Med. 69, 129–144.

Wells, G.A., Scott, A.C., Johnson, C.T., Gunning, R.F., Hancock, R.D., Jeffrey, M., Dawson, M., Bradley, R.,

1987. A novel progressive spongiform encephalopathy in cattle. Vet. Rec. 121, 419–420.

Willesmith, J.W., Wells, G.A.H., Cranwell, M.P., Ryan, J.B.M., 1988. Bovine spongiform encephalopathy:

epidemiological studies. Vet. Rec. 123, 638–644.

A. Allepuz et al. / Preventive Veterinary Medicine 79 (2007) 174–185 185