Active animal health surveillance in European Union Member States: gaps and opportunities.

Animal health surveillance enables the detection and control of animal diseases including zoonoses. Under the EU-FP7 project RISKSUR, a survey was conducted in 11 EU Member States and Switzerland to describe active surveillance components in 2011 managed by the public or private sector and identify gaps and opportunities. Information was collected about hazard, target population, geographical focus, legal obligation, management, surveillance design, risk-based sampling, and multi-hazard surveillance. Two countries were excluded due to incompleteness of data. Most of the 664 components targeted cattle (26·7%), pigs (17·5%) or poultry (16·0%). The most common surveillance objectives were demonstrating freedom from disease (43·8%) and case detection (26·8%). Over half of components applied risk-based sampling (57·1%), but mainly focused on a single population stratum (targeted risk-based) rather than differentiating between risk levels of different strata (stratified risk-based). About a third of components were multi-hazard (37·3%). Both risk-based sampling and multi-hazard surveillance were used more frequently in privately funded components. The study identified several gaps (e.g. lack of systematic documentation, inconsistent application of terminology) and opportunities (e.g. stratified risk-based sampling). The greater flexibility provided by the new EU Animal Health Law means that systematic evaluation of surveillance alternatives will be required to optimize cost-effectiveness.

A Simulation Model to Determine Sensitivity and Timeliness of Surveillance Strategies.

Animal surveillance systems need regular evaluation. We developed an easily applicable simulation model of the German wild boar population to investigate two evaluation attributes: the sensitivity and timeliness (i.e. the ability to detect a disease outbreak rapidly) of a surveillance system. Classical swine fever (CSF) was used as an example for the model. CSF is an infectious disease that may lead to massive economic losses. It can affect wild boar as well as domestic pigs, and CSF outbreaks in domestic pigs have been linked to infections in wild boar. Awareness of the CSF status in wild boar is therefore vital. Our non-epidemic simulation model is based on real data and evaluates the currently implemented German surveillance system for CSF in wild boar. The results show that active surveillance for CSF fulfils the requirements of detecting an outbreak with 95% confidence within one year after the introduction of CSF into the wild boar population. Nevertheless, there is room for improved performance and efficiency by more homogeneous (active and passive) sampling of wild boar over the year. Passive surveillance alone is not sufficient to meet the requirements for detecting the infection. Although CSF was used as example to develop the model, it may also be applied to the evaluation of other surveillance systems for viral diseases in wild boar. It is also possible to compare sensitivity and timeliness across hypothetical alternative or risk-based surveillance strategies.

Highly Pathogenic Avian Influenza H5N8 in Germany: Outbreak Investigations.

Epidemiological outbreak investigations were conducted in highly pathogenic avian influenza virus of the subtype H5N8 (HPAIV H5N8)-affected poultry holdings and a zoo to identify potential routes of entry of the pathogen via water, feedstuffs, animals, people, bedding material, other fomites (equipment, vehicles etc.) and the presence of wild birds near affected holdings. Indirect introduction of HPAIV H5N8 via material contaminated by infected wild bird seems the most reasonable explanation for the observed outbreak series in three commercial holdings in Mecklenburg-Western Pomerania and Lower Saxony, while direct contact to infected wild birds may have led to outbreaks in a zoo in Rostock and in two small free-range holdings in Anklam, Mecklenburg-Western Pomerania.

An approach to model monitoring and surveillance data of wildlife diseases-exemplified by Classical Swine Fever in wild boar.

The analysis of epidemiological field data from monitoring and surveillance systems (MOSSs) in wild animals is of great importance in order to evaluate the performance of such systems. By parameter estimation from MOSS data, conclusions about disease dynamics in the observed population can be drawn. To strengthen the analysis, the implementation of a maximum likelihood estimation is the main aim of our work. The new approach presented here is based on an underlying simple SIR (susceptible-infected-recovered) model for a disease scenario in a wildlife population. The three corresponding classes are assumed to govern the intensities (number of animals in the classes) of non-homogeneous Poisson processes. A sampling rate was defined which describes the process of data collection (for MOSSs). Further, the performance of the diagnostics was implemented in the model by a diagnostic matrix containing misclassification rates. Both descriptions of these MOSS parts were included in the Poisson process approach. For simulation studies, the combined model demonstrates its ability to validly estimate epidemiological parameters, such as the basic reproduction rate R0. These parameters will help the evaluation of existing disease control systems. They will also enable comparison with other simulation models. The model has been tested with data from a Classical Swine Fever (CSF) outbreak in wild boars (Sus scrofa scrofa L.) from a region of Germany (1999-2002). The results show that the hunting strategy as a sole control tool is insufficient to decrease the threshold for susceptible animals to eradicate the disease, since the estimated R0 confirms an ongoing epidemic of CSF.

Towards a new, ecologically targeted approach to monitoring wild bird populations for avian influenza viruses.

Prevalence monitoring of avian influenza in wild bird populations is important to estimate risks for the occurrence of potentially zoonotic and economically disastrous outbreaks of highly pathogenic avian influenza virus (AIV) in poultry worldwide. A targeted, cost-effective monitoring method for AIV in wild birds was developed, which is based on monitoring results for AIV in Germany and information on the distribution and abundance of wild bird species in selected habitat types. Spatial data were combined with virological and outbreak data for the period of 1 January 2006 to 31 December 2010. Using Germany as an example, we identified 11 indicator species. By concentrating monitoring efforts on these species in spatially confined locations, we propose a targeted and more cost-effective risk-based AIV monitoring approach that can be adapted universally for the identification of wild bird indicator species worldwide with the perspective of reducing sample sizes (and costs) without impairing the validity of the results.

Epidemiological and ornithological aspects of outbreaks of highly pathogenic avian influenza virus H5N1 of Asian lineage in wild birds in Germany, 2006 and 2007.

In Germany, two distinct episodes of outbreaks of highly pathogenic avian influenza virus of subtype H5N1 (HPAIV H5N1) in wild birds occurred at the beginning of 2006, and in summer 2007. High local densities of wild bird populations apparently sparked clinically detectable outbreaks. However, these remained restricted in (i) number of birds, (ii) species found to be affected, (iii) time, and (iv) location despite the presence of several hundred thousands of susceptible wild birds and further stressors (food shortage, harsh weather conditions and moulting). Northern and southern subpopulations of several migratory anseriform species can be distinguished with respect to their preference for wintering grounds in Germany. This corroborates viral genetic data by Starick et al. (2008) demonstrating the introduction of two geographically restricted virus subpopulations of Qinghai-like lineage (cluster 2.2.A and 2.2.B) into northern and southern Germany, respectively, in 2006. The incursion of virus emerging in 2007, found to be distinct from the clusters detected in 2006 (Starick et al., 2008), may have been associated with moulting movements. Intensive past-outbreak investigations with negative results of live and dead wild birds and of terrestrial scavengers excluded continued circulation of virus on a larger scale. However, persistence of virus in small pockets of local wild bird populations could not be ruled out resiliently. 1.5% of investigated sera originating from cats sampled at the epicentres of the Ruegen 2006-outbreak contained H5-antibodies. Passive monitoring was found to be highly superior to live bird surveillance when aiming at the detection of HPAIV H5N1 in wild birds (P < 0.0001).

Assessment of international inter-laboratory comparison tests for the diagnosis of classical swine fever from 1998 until 2007.

The inter-laboratory comparison tests for classical swine fever (CSF) laboratory diagnosis organised by the European Community Reference Laboratory for CSF are regularly performed within European Union Member States. The objective of this study was to evaluate the results of the inter-laboratory comparison tests carried out over the last decade, from 1998 until 2007, by using a statistical approach. A set of five or six lyophilised sera was sent to participants. These included sera containing CSF antibodies, sera containing antibodies against ruminant pestiviruses, sera containing CSF virus and negative sera. This study focused on the results of the diagnostic reference methods for CSF: the neutralisation test for the detection of CSF antibodies (including its interpretation) and virus isolation for the detection of CSF virus. For the detection of CSF antibodies, results were closest to what was expected by the Community Reference Laboratory when only neutralisation tests were performed. The percentage of correct results decreased as soon as the results of CSF antibody enzyme-linked immunosorbent assay were included or when sera with antibodies to ruminant pestiviruses were added to the panel. The results for the detection of CSF antibodies are still valid today, as no additional method has been introduced recently. Regarding CSF virus detection, CSF virus isolation is well established but on the way to being superseded as the reference test by reverse-transcription polymerase chain reaction.

Possible routes of introduction of bluetongue virus serotype 8 into the epicentre of the 2006 epidemic in north-western Europe.

In August 2006, bluetongue (BT) was notified in The Netherlands on several animal holdings. This was the onset of a rapidly spreading BT-epidemic in north-western Europe (latitude >51 degrees N) that affected cattle and sheep holdings in The Netherlands, Belgium, Germany, France and Luxembourg. The outbreaks were caused by bluetongue virus (BTV) serotype 8, which had not been identified in the European Union before. Bluetongue virus can be introduced into a free area by movement of infected ruminants, infected midges or by infected semen and embryos. In this study, information on animal movements or transfer of ruminant germ plasms (semen and embryos) into the Area of First Infection (AFI), which occurred before and during the onset of the epidemic, were investigated in order to establish the conditions for the introduction of this virus. All inbound transfers of domestic or wild ruminants, non-susceptible mammal species and ruminant germ plasms into the AFI during the high-risk period (HRP), registered by the Trade Control and Expert System (TRACES) of the EC, were obtained. Imports originating from countries with a known or suspected history of BTV-incidence of any serotype were identified. The list of countries with a reported history of BTV incidence was obtained from the OIE Handistatus II for the period from 1996 until 2004. No ruminants were imported from a Member State (MS) with a known history of BTV-8 or from any other country with a known or suspected history of BTV incidence of any serotype. Of all non-susceptible mammal species only 233 horses were transported directly into the AFI during the HRP. No importations of semen or embryos into the AFI were registered in TRACES during the period of interest. An obvious source for the introduction of BTV-8, such as import of infected ruminants, could not be identified and the exact origin and route of the introduction of BTV-8 thus far remains unknown. However, the absence of legal import of ruminants from outside the EU into the AFI and the absence of BTV-8 in southern Europe suggest that, the introduction of the BTV-8 infection into the north-western part of Europe took place via another route. Specifically, in relation to this, the potential for Culicoides to be imported along with or independently of the import of animals, plants or other 'materials', and the effectiveness of measures to reduce such a possibility, merit further study.

Impact of human interventions on the spread of bluetongue virus serotype 8 during the 2006 epidemic in north-western Europe.

Bluetongue virus (BTV) can be spread by movement or migration of infected ruminants. Infected midges (Culicoides sp.) can be dispersed with livestock or on the wind. Transmissions of infection from host to host by semen and trans-placental infection of the embryo from the dam have been found. As for any infectious animal disease, the spread of BTV can be heavily influenced by human interventions preventing or facilitating the transmission pathways. This paper describes the results of investigations that were conducted on the potential role of the above-mentioned human interventions on the spread of BTV-8 during the 2006 epidemic in north-western Europe. Data on surveillance and control measures implemented in the affected European Union (EU) Member States (MS) were extracted from the legislation and procedures adopted by the national authorities in Belgium, France, Germany, and The Netherlands. The impact of the control measures on the BTV-incidence in time and space was explored. Data on ruminant transports leaving the area of first infection (AFI) to other areas within and beyond the affected MS were obtained from the national identification and registration systems of the three initially affected MS (Belgium, Germany, The Netherlands) and from the Trade Control and Expert System (TRACES) of the European Commission. The association between the cumulative number of cases that occurred in a municipality outside the AFI and the number of movements or the number of animals moved from the AFI to that municipality was assessed using a linear negative binomial regression model. The results of this study indicated that the control measures which were implemented in the affected MS (in accordance with EU directives) were not able to fully stop further spread of BTV and to control the epidemic. This finding is not surprising because BT is a vector-borne disease and it is difficult to limit vector movements. We could not assess the consequences of not taking control measures at all but it is possible, if not most likely, that this would have resulted in even wider spread. The study also showed an indication of the possible involvement of animal movements in the spread of BTV during the epidemic. Therefore, the prevention of animal movements remains an important tool to control BTV outbreaks. The extension of the epidemic to the east cannot be explained by the movement of animals, which mainly occurred in a north-western direction. This indicates that it is important to consider other influential factors such as dispersal of infected vectors depending on wind direction, or local spread.

Modelling local dispersal of bluetongue virus serotype 8 using random walk.

The knowledge of the place where a disease is first introduced and from where it later spreads is a key element for the understanding of an epizootic. For a contagious disease, the main method is back tracing. For a vector-borne disease such as the Bluetongue virus serotype 8 epizootic that occurred in 2006 in North-Western Europe, the efficiency of tracing is limited because many infected animals are not showing clinical signs. In the present study, we propose to use a statistical approach, random walk, to model local spread in order to derive the Area of First Infection (AFI) and spread rate. Local spread is basically described by the random movements of infected insect vectors. Our model localised the AFI centre, origin of the infection, in the Netherlands, South of Maastricht. This location is consistent with the location of the farms where the disease was first notified in the three countries (Netherlands, Belgium, and Germany) and the farm where retrospectively the earliest clinical signs were found. The derived rate of spread of 10-15 km/week is consistent with the rates observed in other Bluetongue epizootics. In another article Mintiens (2008), the AFI definition has then been used to investigate possible ways of introduction (upstream tracing) and to study the effect of animal movements from this area (downstream tracing).

Establishing the spread of bluetongue virus at the end of the 2006 epidemic in Belgium.

Bluetongue (BT) was notified for the first time in several Northern European countries in August 2006. The first reported outbreaks of BT were confirmed in herds located near the place where Belgium, The Netherlands and Germany share borders. The disease was rapidly and widely disseminated throughout Belgium in both sheep and cattle herds. During the epidemic, case reporting by the Veterinary Authorities relied almost exclusively on the identification of herds with confirmed clinical infected ruminants. A cross-sectional serological survey targeting all Belgian ruminants was then undertaken during the vector-free season. The first objective of this study was to provide unbiased estimates of BT-seroprevalence for different regions of Belgium. Since under-reporting was suspected during the epidemic, a second goal was to compare the final dispersion of the virus based on the seroprevalence estimates to the dispersion of the confirmed clinical cases which were notified in Belgium, in order to estimate the accuracy of the case detection based on clinical suspicion. True within-herd seroprevalence was estimated based on a logistic-normal regression model with prior specification on the diagnostic test's sensitivity and specificity. The model was fitted in a Bayesian framework. Herd seroprevalence was estimated using a logistic regression model. To study the linear correlation between the BT winter screening data and the case-herds data, the linear predicted values for the herd prevalence were compared and the Pearson correlation coefficient was estimated. The overall herd and true within-herd seroprevalences were estimated at 83.3 (79.2-87.0) and 23.8 (20.1-28.1)%, respectively. BT seropositivity was shown to be widely but unevenly distributed throughout Belgium, with a gradient decreasing towards the south and the west of the country. The analysis has shown there was a strong correlation between the outbreak data and the data from the survey (r=0.73, p<0.0001). The case detection system based on clinical suspicion underestimated the real impact of the epidemic, but indicated an accurate spatial distribution of the virus at the end of the epidemic.

Phylogenetic analyses of highly pathogenic avian influenza virus isolates from Germany in 2006 and 2007 suggest at least three separate introductions of H5N1 virus.

In spring 2006, highly pathogenic avian influenza virus (HPAIV) of subtype H5N1 was detected in Germany in 343 dead wild birds, as well as in a black swan (Cygnus atratus) kept in a zoo, three stray cats, one stone marten (Martes foina), and in a single turkey farm. In 2007 (June-July) the virus reoccurred in 96 wild birds at six geographically separate locations in the Southeast of Germany. In addition, a backyard mixed duck and goose holding was affected. Real-time RT-PCR [Hoffmann, B., Harder, T., Starick, E., Depner, K., Werner, O., Beer, M., 2007. Rapid and highly sensitive pathotyping of avian influenza A H5N1 virus by using real-time reverse transcription-PCR. J. Clin. Microbiol. 45, 600-603] and nucleotide sequencing confirmed that these H5-viruses belonged to the Qinghai lineage of HPAIV H5N1 (clade 2.2). For a more detailed analysis, the hemagglutinin and neuraminidase genes of 27 selected German H5N1 viruses isolated 2006 or 2007 and originating from different regions and animal species were sequenced and analysed phylogenetically. As a result, three closely related but distinguishable H5N1 subclades could be defined: In 2006 a 'Northern type' (subclade 2.2.2), representing virus isolates from the German federal states Mecklenburg-Western Pomerania, Schleswig-Holstein, Brandenburg, and Lower Saxony, and a 'Southern type' (subclade 2.2.1) from Baden-Württemberg and Bavaria were detected. Interestingly, representatives of both types were present in Central Germany and caused the outbreak in turkeys (subclade 2.2.2) and in a case in a tufted duck (Aythya fuligula) (subclade 2.2.1) in Saxony. Furthermore, one isolate from the South of Germany was identified as 2.2.2 and vice versa a 2.2.1-like isolate was found in Northern Germany. H5N1 viruses isolated in 2007 belonged to a third type (subclade 2.2.3) which was not detected in 2006. Our data suggest the introduction of three distinct H5N1 variants into the wild bird population of Germany. The source of these viruses and the exact time of introduction remain obscure. Based on the identification of closely related H5N1 viruses from Southern and Central Russia, a recent introduction via wild birds on winter escape from these regions, early in 2006 constitutes the most likely scenario for the 2006 outbreaks. The viruses detected in 2007 most likely represent another new incursion from an as yet unknown source.

A simple statistical approach for assessing inter-laboratory comparison tests for classical swine fever diagnosis.

The aim of this study was to compare on an objective basis the results obtained during five classical swine fever (CSF) ring tests conducted in Germany between 1999 and 2003. A novel and simple statistical approach used in behavioural sciences was used. For each ring test, the regional laboratories received a panel of five lyophilized pig sera. The panel contained CSF virus positive and negative samples. The final task of the laboratory was to ascertain if a serum sample was positive for CSF or not. Some sera were very easy to diagnose as CSF positive while some sera had border line values and proved to be challenging. Depending on the degree of difficulty the sera were divided into five categories. The evaluation of the ring test results was performed using a scoring system based on a score from -3 to +3 which takes into consideration the degree of difficulty to produce a correct diagnosis. To compare the results between different laboratories and/or between different ring tests more easily the total score of one laboratory was expressed in percentage. The final analysis of the data showed that the CSF diagnostic quality improved continuously.

Animal disease outbreak control: the use of crisis management tools.

In this era of globalisation the effective control of animal disease outbreaks requires powerful crisis management tools. In the 1990s software packages for different sectors of the government and agricultural industry began to be developed. In 2004, as a special application for tracking the movement of animals and animal products, the European Union developed the Trade Control and Expert System (TRACES) on the basis of its predecessor, the ANImal MOvement (ANIMO) project. The nationwide use of the ANIMO system by the veterinary authorities in Germany marked the beginning of the development in 1993 of a computerised national animal disease reporting system--the TierSeuchenNachrichten (TSN)--using the ANIMO hardware and software components. In addition to TRACES and TSN the third pillar for the management of animal disease outbreaks and crises in Germany is the national cattle and swine database--called Herkunftssicherungs- und Informationssystem für Tiere. A high degree of standardisation is necessary when integrating the different solutions at all levels of government and with the private sector. In this paper, the authors describe the use of these tools on the basis of their experience and in relation to what we can do now and what we should opt for in the future.

Long-term studies on maternal immunity for Aujeszky's disease and classical swine fever in wild boar piglets.

The aim of the studies was to fathom the duration and the role of maternal immunity for Aujeszky's disease (AD) and classical swine fever (CSF) in wild boar offspring. In one experiment, two wild boar sows were infected with a low pathogenic pseudorabies virus (PRV) in 1999. A total of 51 offspring was born between 1999 and 2002 and was monitored for PRV maternal antibodies. In a second experiment, the maternal immunity for CSF was analysed. Therefore, a sow was orally vaccinated against CSF using vaccine baits containing the live-attenuated C-strain vaccine. The vaccination took place in January 1999. The sow gave birth to four piglets in 2001 and to two piglets in 2002. With respect to maternal immunity for AD, some piglets reacted positive in the ELISA up to 27-week post-partum while in the neutralization test antibodies were detected up to 15-week post-partum. The calculated half-life of neutralizing antibodies was 21 days. Regarding CSF, the neutralization titres of maternal antibodies dropped continuously reaching values of < or =10 ND50 20-week post-partum. After the 12th week post-partum, most of the sera reacted negative in the ELISA. However, after the third month, low levels of neutralization titres were still detectable. The results are discussed with respect to the epidemiology and control of both diseases in wild boar populations.

Potential risk factors for bovine Neospora caninum infection in Germany are not under the control of the farmers.

In the German state of Rhineland-Palatinate, herds were identified that were likely to have a Neospora caninum sero-prevalence > or = 10% by using a bulk milk ELISA. Individual herd data were obtained by a questionnaire. Univariate logistic regression showed that bulk milk positive farms had a significantly higher chance to report an increased abortion rate than negative farms (P(Wald)<0.1). The chance to have a bulk milk positive herd increased with the minimum number of years a farm had reported an increased abortion rate (P(Wald)<0.1). Questionnaire data, population and dog density as well as climatic data specific for the farm localization were used to identify potential risk factors for a herd to have acquired N. caninum infections. Within an optimized multiple logistic regression model 'Number of farm dogs', 'Herd size', and factors related to the municipality the farm was localized, i.e. 'Mean temperature in July', and 'Dog density' were significant risk factors (P(Wald)<0.1). The present study underlines the role farm dogs have in the epidemiology of neosporosis. In addition, it suggests that the risk a herd has to acquire N. caninum infections is also associated with factors related to the farm location, i.e. factors that are largely out of the control of farmers.

Adaptation of a commercial ELISA for the detection of antibodies against Neospora caninum in bovine milk.

The aim of the present study was to determine whether a commercially available ELISA could be used to examine bovine milk for antibodies against Neospora caninum. In an initial titration experiment, a milk dilution of 1:2 was found optimal to obtain milk results that were linearly correlated to those obtained with corresponding sera. This dilution was then used to examine 791 milk samples from N. caninum infected herds in the commercial ELISA. Milk results of individual animals were compared with those obtained by the same ELISA for the corresponding serum samples. The linear correlation between milk and serum antibody results of individual animals was characterized by R2 = 0.702. Multiple linear regression indicated that the later the stage of lactation at which an animal was sampled, the higher the milk ELISA result was as compared to the serum ELISA result. The examination of the two-graph receiver operating characteristics revealed an optimal cut-off of 0.261 to obtain similar results in the examination of milk and serum. With this cut-off, the test had a sensitivity and specificity relative to the serum results of 90%. The milk-based commercial ELISA classified more aborting dams as positive than the serum-based ELISA with this cut-off. The milk ELISA may be a valuable tool to assess the herd status with regard to abortion caused by N. caninum.

Processes leading to a spatial aggregation of Echinococcus multilocularis in its natural intermediate host Microtus arvalis.

The small fox tapeworm (Echinococcus multilocularis) shows a heterogeneous spatial distribution in the intermediate host (Microtus arvalis). To identify the ecological processes responsible for this heterogeneity, we developed a spatially explicit simulation model. The model combines individual-based (foxes, Vulpes vulpes) and grid-based (voles) techniques to simulate the infections in both intermediate and definite host. If host populations are homogeneously mixed, the model reproduces field data for parasite prevalence only for a limited number of parameter combinations. As ecological parameters inevitably vary to a certain degree, we discarded the homogeneous mixing model as insufficient to gain insight into the ecology of the fox tapeworm cycle. We analysed five different model scenarios, each focussing on an ecological process that might be responsible for the heterogeneous spatial distribution of E. mulitlocularis in the intermediate host. Field studies revealed that the prevalence ratio between intermediate and definite host remains stable over a wide range of ecological conditions. Thus, by varying the parameters in simulation experiments, we used the robustness of the agreement between field data and model output as quality criterion for the five scenarios. Only one of the five scenarios was found to reproduce the prevalence ratio over a sufficient range of parameter combinations. In the accentuated scenario most tapeworm eggs die due to bad environmental conditions before they cause infections in the intermediate host. This scenario is supported by the known sensitivity of tapeworm eggs to high temperatures and dry conditions. The identified process is likely to lead to a heterogeneous availability of infective eggs and thus to a clumped distribution of infected intermediate hosts. In conclusion, areas with humid conditions and low temperatures must be pointed out as high risk areas for human exposure to E. multilocularis eggs as well.

Regional distribution of bovine Neospora caninum infection in the German state of Rhineland-Palatinate modelled by Logistic regression.

To obtain a rapid overview over the distribution of bovine Neospora caninum-infections in the German state of Rhineland-Palatinate, an ELISA to determine specific bovine antibodies against a p38 surface antigen of N. caninum tachyzoites was modified to examine bulk milk samples from cattle herds. Experimental bulk milk samples were used to demonstrate that the seroprevalence in a group of animals can be estimated with this ELISA. A cut-off was selected for the specific detection of herds having a seroprevalence > or =10%. About 90% of the dairy herds located in Rhineland-Palatinate were examined. An overall prevalence of bulk milk-positive herds of 7.9% (95% confidence interval 7.0-8.9%), respectively, was determined. Major regional differences in the distribution of bulk milk-positive herds were observed. Prevalences were higher in regions with an increased degree of urbanisation. Logistic regression was applied to model the prevalence of bulk milk-positive herds on a district and city level. Variables describing the dog density, mean temperature in July, mean temperature in January and the total yearly precipitation in districts and cities were able to explain most of the observed variability in the regional prevalences. Our results provide evidence that in addition to risk factors related to individual farms also risk factors related to the farm location such as dog density in the surrounding and climate factors are important in the epidemiology of bovine neosporosis.

A Bayesian model for spatial wildlife disease prevalence data.

The analysis of the geographical distribution of disease on the scale of geographic areas such as administrative boundaries plays an important role in veterinary epidemiology. Prevalence estimates of wildlife population surveys are often based on regional count data generated by sampling animals shot by hunters. The observed disease rate per spatial unit is not an useful estimate of the underlying disease prevalence due to different sample sizes and spatial dependencies between neighbouring areas. Therefore, it is necessary to account for extra-sample variation and spatial correlations in the data to produce more accurate maps of disease incidence. The detection of spatial patterns is complicated by missing data in many of the geographical areas as the complete coverage of all areas is nearly impossible in wildlife surveys. For this purpose a hierarchical Bayesian model in which structured and unstructured over dispersion is modelled explicitly in terms of spatial and non-spatial components was implemented by Markov chain Monte Carlo methods. The model was empirically compared with the results of a non-spatial beta-binomial model using surveillance data of pseudorabies virus infections of European wild boars (Sus scrofa scrofa L.) in the Federal State of Brandenburg, Germany.