In this study we aimed to explore the nature and extent of the association between potential risk factors and TB occurrence in wild ungulates and cattle in one of the most TB-prevalent regions of Spain referred to as Ciudad Real. The proportion of cattle farms becoming bTB positive in 2006, the mean number of hunting seasons in which the hunting estates of the municipality have been inspected and the apparent prevalence of TB in wild boar in 2006 were identified as the most relevant factors related to the TB occurrence in 2007 in Ciudad Real. These factors are useful predictors in planning disease control strategies. Results revealed that both livestock- and wildlife-related factors determine TB presence at spatial scale. Overall, the major risk factor for TB incidence in any given year is whether it was present or not, and at what level, in the previous year.
The probability of TB occurrence in Ciudad Real resembled the biogeography of the province as well as game and cattle farming distribution, with areas at high risk concentrated in the municipalities with a higher proportion of forest or natural habitats (Toledo Mountains in the Northwest corner, the Guadiana valley in the East, and Sierra Morena in the South), and the highest big game activity. In fact, the mean number of hunting seasons in which the hunting estates of the municipality have been inspected, which is an indicator of the hunting activity in the municipality, remained statistically significant in the model (see below). Usually, woodlands and savannah-like areas (locally called dehesas) are dedicated to big game, whereas marginal dehesas are located in the valleys in close proximity, where land is not appropriate for agriculture, are mainly dedicated to extensive livestock farming. This distribution, together with particular Mediterranean features that favour the wildlife-livestock interface (i.e. water areas or pasture sharing) may explain how TB could be transmitted from wildlife to livestock and vice versa (Figures
to
). However, from this study we cannot infer the directionality of M. bovis transmission, i.e. whether wildlife reservoirs are infecting cattle, or whether cattle is the responsible of the circulation of M. bovis in both domestic and wild hosts. In fact, it could be the case that some municipalities with a high prevalence of TB in just one species (for example, wild boar) in 2007 may be purely correlated with a high prevalence of TB in only that species (in the example, with no red deer nor cattle infected in that municipality) the previous year. This would indicate no inter-species transmission in some regions. However, Ciudad Real municipalities with this scenario are an exception (9 out of 113) and many TB-infected regions presented TB cases in more than one species (44.19% in 2006 and 28.86% in 2007) (Table
). This suggests a potential multi-species interaction scenario. Unfortunately, we cannot prove this because the final model did not include any interaction between variables related to hosts. Nevertheless, future studies should reveal whether the presence of the disease in wildlife is associated with increased presence of the disease in livestock and establish the directionality and extent of the TB inter-species transmission.
| Table 2Number of municipalities of Ciudad Real that were TB positive in 2006 and 2007 in either red deer (RD), wild boar (WB), cattle (Bov) or any of their combinations |
The finding that municipalities with a high proportion of cattle farms becoming bTB positive in 2006 were at high risk for TB occurrence in 2007 (OR

=

1.86; 95% CI

=

1.06-3.39) is an indicator that TB until 2007 repeatedly tends to appear in the same municipalities. These findings are in agreement with the trend of incidence and persistence of bTB in South Central Spain during 2006–2009, particularly in Ciudad Real, observed in previous studies
[
14]. This indicates the persistence of the pathogen over consecutive sanitary campaigns despite the eradication efforts and the culling of positive animals. Herd-level research is needed to elucidate whether barriers imposed to prevent the transmission of
M. bovis into bTB-free farms are not as efficient as expected, or diagnostics were not reliable enough in presumed free farms. Both of these risk factors have not been explored in this study. Most of the extensive farms and cattle census in Ciudad Real province are located in municipalities where some of the risk factors identified in this model may operate, such as wildlife TB reservoir abundance (see below). Although the TB inspection in Spain is compulsory in all cattle farms, these aspects also show that the efforts in controlling
M. bovis infection in the whole cattle stock should not be relaxed, especially in extensive farms where enclosing and handling the whole stock is more difficult. Our final model suggests that the higher the number of cattle submitted to the sanitary campaigns, the higher the likelihood of the municipality to be TB positive the following year (OR

=

1.94; CI

=

1.11-3.40). As Brooks-Pollock and Keeling
[
20] reported, many elements associated with herd size could contribute to disease persistence within a herd, such as an increased number of movements or larger land coverage with increased risk of environmental contamination, or more densely stocked cattle. Nonetheless, this should be evaluated at the herd level.
Although the information regarding TB prevalence in wildlife is usually not available and more difficult to obtain than in cattle, we believe that it is also crucial to monitor the TB status of wild reservoirs in a region
[
19]. In fact, one of the significant covariates in the final model is the mean number of hunting seasons in which the hunting estates of the municipality have been inspected (OR

=

1.69; 90% CI

=

1.19-2.42), which is related to the intensity and sustainability of the hunting activity performed in each estate over time, and therefore the abundance of big game. In addition, the analysis revealed two additional major risk factors related to wild hosts: the apparent prevalence of TB in wild boar (OR

=

1.94; 95% CI

=

1.20-3.59) and the number of TB-positive red deer (OR

=

1.69; 90% CI

=

1.05-2.90) both in the previous year. The implication of wild boar and red deer in the TB presence and maintenance in South Central Spain has been previously suggested
[
10]; the wild boar showing higher TB prevalence than red deer
[
9,
21]. In addition, wild boar has been proposed as the most relevant wild host of
M. bovis in Spain
[
10] becoming a true TB reservoir in the Iberian Peninsula
[
22]. This importance is enhanced by its abundance in Europe, the high levels of infection observed in this species, its ability to disseminatethe pathogen, its scavenging behaviour and, mostly, its potential ability for crossing fences and contacting with livestock
[
22]. Given this situation, physical biosafety practices may serve as a means to cost-effectively prevent contact between wild and domestic mammals and thus TB inter-species transmission. This is particularly useful in those areas where the hunting industry plays an important role in the local economy, such as Ciudad Real. Also, any action conducted to reduce TB prevalence and mycobacteria spreading in wild ungulates should contribute to reduce the
M. bovis transmission risk at the wildlife-livestock interface. Options include the management of host density, spatial aggregations at supplementary feeding sites or waterholes, the safe disposal of carrion and viscera by hunters, and oral vaccination
[
5,
21].
There is evidence supporting the inter-species circulation of
M. bovis[
13] and several studies have recently confirmed the presence of the same
M. bovis spoligotypes in cattle and wild fauna sharing the same area
[
8,
11,
22-
26].
M. bovis transmission between wild and domestic animals may occur directly via close contact, or indirectly via contamination of food or the environment with
M. bovis. Most of the bTB control programmes in developed countries are mainly directed towards livestock not including wildlife, even where it is obviously involved in disease maintenance. The lack of integral control strategies is more evident in extensive cattle, which is the sector mostly exposed to wildlife contacts
[
15]. This was supported previously
[
16] and in our results, since the proportion of cattle farms classified as extensive beef breeding farms (OR

=

1.47; 90% CI

=

1.02-2.14) and the number of farms devoted to bullfighting cattle were revealed as risk factors in the final model (although this latter covariate is not highly significant, 90% CI

=

0.97-1.87, probably because there are scarce and very disperse observations). Both types of farms are integrated in natural pasture agrosystems in close proximity with wildlife. However, the inclusion of these two covariates related to extensive cattle farming reinforces the idea that sanitary programs should incorporate the wildlife interface, especially in those cattle farms most exposed to
M. bovis infection, as has been done in Spain since 2011 (
http://rasve.mapa.es/Publica/Programas/Normativa.asp).
The Bayesian mixed effects multivariable logistic regression model was chosen as the best statistical approach to be used in this study. The reason is because the Bayesian methodology solves most of the problems faced by traditional statistical methods, e.g. the spatial autocorrelation, the potential dependence between the covariates or the incorporation of variables with few observations. The unit of analysis (i.e. municipality) was also considered adequate given the information that was available and the spatial level at which policies are taken. However, as any ecological study, some of the results may be biased as a consequence of the artificial grouping of observations and variables at the municipality level. In addition, differences in the municipality size may confound the interpretation of the maps, since the largest municipalities could appear at the highest risk only because they entail the majority of the observations
[
27]. Although variations in size among municipalities are not particularly large in the study area, we have used proportions in the majority of the covariates to minimize this problem. Despite these limitations, the approach used here is very useful for the exploration of spatially aggregated data and to highlight the most risky areas to perform more accurate analysis. The model proposed in this article is robust and consistent, as shown by the much lower DIC of the final model (72.32) and the small SD of S
i (0.1199) and U
i (0.0492). The robustness and consistence of this model allow to study the “TB hot spots” of the province in detail, since future epidemiological analyses at more local scale may be conducted.