Suchergebnisse

SIMPLE SUMMARY: Effectiveness and successful implementation of control measures greatly depend on hunters' willingness and motivation to carry out these measures. Therefore, assessing their opinions regarding the current system is paramount in order to achieve the best possible results. The present study provides insights of hunters' attitudes and perceptions about measures to control African swine fever (ASF) in wild boar in Lithuania. This study highlights several measures that are not supported by hunters (i.e., restriction of hunting, selective female hunting, ban of supplementary feeding, involvement of additional forces in ASF control) and possible motivational options (i.e., reduction of work, financial incentives and improved feedback and relationships with government officials). Considering these findings when planning and altering control measures for ASF could improve their successful implementation in the field. ABSTRACT: After the introduction of African swine fever (ASF) into Lithuania in 2014, continuous spread of the disease resulted in infection of the wild boar populations in most parts of Lithuania. The virus has been moving closer to other Western European countries where pig density is high. An efficient surveillance system detecting ASF cases early in domestic and wild animals is necessary to manage this disease. To make surveillance appropriate and effective, it is critical to understand how key players perceive the implemented control measures. This study investigated the attitudes and beliefs of hunters in Lithuania regarding currently implemented or proposed measures for the control of ASF in the wild boar population. Study data were collected through questionnaires distributed via the internet and by hunting associations in Lithuania. In total, 621 fully completed questionnaires were received and analyzed. All measures interfering with extensive hunting, like ban of driven or individual hunting or ban of supplementary feeding were considered as unacceptable and as ineffective measures ...

Objective: Classical Swine Fever (CSF) is a highly contagious viral disease, which affects all suid species. CSF infection in wild boar can play an important role in disease introduction to commercial pig holdings. Due to its high economic impact, efficient but also cost-effective surveillance strategies have to be implemented not only in commercial pig holdings but also in wild boar. In Germany, the last CSF outbreak occurred in wild boar in 2009. Consequently, vaccination had been implemented until 2012. Since June 2012, Germany is considered to be free from CSF. Following this, active surveillance in wild boar has been carried out according to the directives of the European Union (Council directive 2001/89/EC). Germany's implementation of these regulations plan to take 59 samples per district per year to be capable to demonstrate freedom from disease on district level (conventional method). Compared to conventional surveillance, risk-based surveillance approaches may achieve similar performance at lower cost or better performance at the same cost. Within the framework of the European project RISKSUR (http://www.fp7-risksur.eu/) we conducted a simulation study to compare the performances of different surveillance approaches for CSF in an unvaccinated wild boar population in an area free from the disease. The aim of the study was to find out whether surveillance with the objective of demonstrating freedom from disease in wild boar could be designed more effectively using risk-based or alternative methods compared to using conventional methods. Methods: For the simulation model, R (www.r-project.org) was used for statistical computing and displaying graphs. A virtual wild boar population was generated and an infection initiated within this population. As study area we used the federal state of Rhineland Palatinate. The population size estimates for the considered region, determined using fecal DNA samples, were used to calculate the total number of wild boar within the simulation study. To assure a general pattern of the population structure we chose districts from three areas with different epidemiological situations. The simulated population was structured containing information on age, gender and the type of carcass (shot healthy, shot sick, injured through road traffic accident and found dead). The setup of the infection was done on the basis of data from Mecklenburg-Western Pomerania to estimate the increase of the seroprevalence at the beginning of an infection. The risk factor analysis used to define the risk-based surveillance approaches was done through literature search, expert opinion and bivariate analysis of infection data. Due to a lack of appropriate information in Rhineland Palatinate, infection data of the federal state of Mecklenburg-Western Pomerania were used as data basis as well. The simulation was conducted on the basis of real hunting data of Rhineland Palatinate and the surveillance approach, performed following the regulations of the European Union was simulated With these simulations, the probability of case detection and the time until the first case detection were determined and used as reference values. These values were then compared to the values resulting from the simulation of different alternative and risk-based surveillance methods. Alternative surveillance methods were increased sampling in the age class at higher risk of infection or in the season with an assumed higher detection probability. Furthermore we simulated the sampling in dependence of the population density in the different districts in two different ways. One approach was to sample only in districts were the population density was above a predefined threshold, whereas the other approach was to determine the sample size in the individual districts in dependence of the population density. Results: The results of the fecal DNA analyses showed an estimated mean of 2,593 wild boar per district with a maximum of 8,524 and a minimum of 30 wild boar (median: 2,163). The real hunting data collected in specified districts (27 districts) of Rhineland Palatinate between 2003 and 2014 constituted the basis for the age and sex structure of the simulated population. In total we had 105,439 records. In the analyzed data the sex proportion of shot male and female animals was almost equal (male: 52.4%; female: 47.6%). The age distribution showed that the number of shot animals aged less than one year were highest (55.1%) and the number of samples coming from animals over 2 years was lowest (10.8%). Almost all samples (99.6%) were collected from hunted healthy animals, i.e. from active surveillance. Most samples were taken in the months of November (15.92%), December (13.68%) and January (12.57%). For the simulation of hunting, averaged values of the hunting bag data from 2003-2011 were used. In average 1,340 wild boar/district/year were hunted (min: 0; max: 4,573; median: 1,113). For the setup of the infection into the simulated population, data from Mecklenburg-Western Pomerania were used. They consisted of 17,492 data sets resulting from the years 1993 and 1994, which were collected in six non-vaccination districts. Within this dataset, 2,652 samples had tested seropositive for CSF. Due to the low number of positive cases identified through serological and virological testing in the data set of Rhineland-Palatinate, surveillance data from non-vaccination districts within Mecklenburg-Western Pomerania were used for risk analysis. The data consisted of 85,105 data sets from 1994-2000. The sex, age and carcass distribution showed a similar pattern as the data from Rhineland-Palatinate. Bivariate analysis showed that age plays a role in the probability of being serologically or virologically positive. These findings were supported by the findings of the literature search as well as by expert opinion. In the literature, it was found that the probability of samples gathered through passive surveillance being positive is assumed to be higher. However, the low number of available passive surveillance data made it impossible to support this assumption through statistical analysis. Additionally, experts suggest that seasonality of the hunting and infection as well as population density may be considered as risk factors for infection. The following initial results refer to simulations in a defined area of Rhineland Palatinate consisting of three neighboring districts. From 1000 simulation repetitions of sampling 59 samples per district over the year, by serological examination the infection was detected 1000 times per district (reference value for detection probability). On average 331 cases were detected in the first month of infection (reference value for time until first case is detected). By serological investigations of 59 animals aged less than 1 year infection was not detected at all in 11 simulation runs. On average 162 cases were detected within the first month. However, investigating 59 animals aged over 2 years serologically, the infection was detected 1000 times and 688 times already in the first month of infection. Conclusion: The first results of the simulation model indicate that alternative surveillance strategies show a similar probability of detection. However, serological surveillance of animals aged over two years reduced the time until the first case was detected significantly. Additionally, it might be assumed that through changes in sampling strategies e.g. based on population density thresholds, a reduction of costs is possible. The resulting financial resources could be used to increase sampling following the risk based approaches, therefore increasing the detection probability. They could also be used for campaigns supporting for example passive surveillance. However, the effectiveness of the single surveillance approaches should not only be measured by the outputs of the model, but also through a comprehensive evaluation of the whole surveillance system, including acceptability and practicability of the system. Moreover, the surveillance could be designed taking different risk factors into account and could therefore have the potential to result in a better performance. If higher numbers of animals found dead were investigated, passive surveillance would be an alternative. However, also in the future it will be difficult to reach higher numbers of samples from passive surveillance. Finally it has to be mentioned that due to the limitation of getting accurate population abundance data in wild life, designing surveillance schemes and the establishment of effective surveillance strategies will always constitute a certain challenge.

23 páginas, 7 tablas, 2 figuras. ; Background: This study aimed to provide a systematic review on the geographical distribution of Echinococcus multilocularis in definitive and intermediate hosts in the European Union (EU) and adjacent countries (AC). The relative importance of the different host species in the life-cycle of this parasite was highlighted and gaps in our knowledge regarding these hosts were identified. Methods: Six databases were searched for primary research studies published from 1900 to 2015. From a total of 2,805 identified scientific papers, 244 publications were used for meta-analyses. Results: Studies in 21 countries reported the presence of E. multilocularis in red foxes, with the following pooled prevalence (PP): low (≤ 1 %; Denmark, Slovenia and Sweden); medium (> 1 % to 10 %; Czech Republic, Estonia, France, Germany, Latvia, Lithuania, Poland, Slovakia, Liechtenstein and Switzerland). Studies from Finland, Ireland, the United Kingdom and Norway reported the absence of E. multilocularis in red foxes. However, E. multilocularis was detected in Arctic foxes from the Arctic Archipelago of Svalbard in Norway. Conclusions: Raccoon dogs (PP 2.2 %), golden jackals (PP 4.7 %) and wolves (PP 1.4 %) showed a higher E. multilocularis PP than dogs (PP 0.3 %) and cats (PP 0.5 %). High E. multilocularis PP in raccoon dogs and golden jackals correlated with high PP in foxes. For intermediate hosts (IHs), muskrats (PP 4.2 %) and arvicolids (PP 6.0 %) showed similar E. multilocularis PP as sylvatic definitive hosts (DHs), excluding foxes. Nutrias (PP 1.0 %) and murids (PP 1.1 %) could play a role in the life-cycle of E. multilocularis in areas with medium to high PP in red foxes. In areas with low PP in foxes, no other DH was found infected with E. multilocularis. When fox E. multilocularis PP was >3 %, raccoon dogs and golden jackals could play a similar role as foxes. In areas with high E. multilocularis fox PP, the wolf emerged as a potentially important DH. Dogs and cats could be irrelevant in the life-cycle of the parasite in Europe, although dogs could be important for parasite introduction into non-endemic areas. Muskrats and arvicolids are important IHs. Swine, insectivores, murids and nutrias seem to play a minor or no role in the life-cycle of the parasite within the EU and ACs. ; This research received funding from the European Food Safety Authority (EFSA; http://www.efsa.europa.eu/) under the grant agreement GP/EFSA/AHAW/2012/01 (Project: Echinococcus multilocularis infection in animals). This work was also supported by the DG SANCO of the European Commission (2015) ; Peer reviewed

Background: Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) are vectors of bluetongue virus (BTV), African horse sickness virus and Schmallenberg virus (SBV). Outbreaks of both BTV and SBV have affected large parts of Europe. The spread of these diseases depends largely on vector distribution and abundance. The aim of this analysis was to identify and quantify major spatial patterns and temporal trends in the distribution and seasonal variation of observed Culicoides abundance in nine countries in Europe. Methods: We gathered existing Culicoides data from Spain, France, Germany, Switzerland, Austria, Denmark, Sweden, Norway and Poland. In total, 31,429 Culicoides trap collections were available from 904 ruminant farms across these countries between 2007 and 2013. Results: The Obsoletus ensemble was distributed widely in Europe and accounted for 83% of all 8,842,998 Culicoides specimens in the dataset, with the highest mean monthly abundance recorded in France, Germany and southern Norway. The Pulicaris ensemble accounted for only 12% of the specimens and had a relatively southerly and easterly spatial distribution compared to the Obsoletus ensemble. Culicoides imicola Kieffer was only found in Spain and the southernmost part of France. There was a clear spatial trend in the accumulated annual abundance from southern to northern Europe, with the Obsoletus ensemble steadily increasing from 4000 per year in southern Europe to 500,000 in Scandinavia. The Pulicaris ensemble showed a very different pattern, with an increase in the accumulated annual abundance from 1600 in Spain, peaking at 41,000 in northern Germany and then decreasing again toward northern latitudes. For the two species ensembles and C. imicola, the season began between January and April, with later start dates and increasingly shorter vector seasons at more northerly latitudes. Conclusion: We present the first maps of seasonal Culicoides abundance in large parts of Europe covering a gradient from southern Spain to northern Scandinavia. The identified temporal trends and spatial patterns are useful for planning the allocation of resources for international prevention and surveillance programmes in the European Union.

BACKGROUND: Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) are small hematophagous insects responsible for the transmission of bluetongue virus, Schmallenberg virus and African horse sickness virus to wild and domestic ruminants and equids. Outbreaks of these viruses have caused economic damage within the European Union. The spatio-temporal distribution of biting midges is a key factor in identifying areas with the potential for disease spread. The aim of this study was to identify and map areas of neglectable adult activity for each month in an average year. Average monthly risk maps can be used as a tool when allocating resources for surveillance and control programs within Europe. METHODS: We modelled the occurrence of C. imicola and the Obsoletus and Pulicaris ensembles using existing entomological surveillance data from Spain, France, Germany, Switzerland, Austria, Denmark, Sweden, Norway and Poland. The monthly probability of each vector species and ensembles being present in Europe based on climatic and environmental input variables was estimated with the machine learning technique Random Forest. Subsequently, the monthly probability was classified into three classes: Absence, Presence and Uncertain status. These three classes are useful for mapping areas of no risk, areas of high-risk targeted for animal movement restrictions, and areas with an uncertain status that need active entomological surveillance to determine whether or not vectors are present. RESULTS: The distribution of Culicoides species ensembles were in agreement with their previously reported distribution in Europe. The Random Forest models were very accurate in predicting the probability of presence for C. imicola (mean AUC = 0.95), less accurate for the Obsoletus ensemble (mean AUC = 0.84), while the lowest accuracy was found for the Pulicaris ensemble (mean AUC = 0.71). The most important environmental variables in the models were related to temperature and precipitation for all three groups. CONCLUSIONS: The duration ...

Background Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) are small hematophagous insects responsible for the transmission of bluetongue virus, Schmallenberg virus and African horse sickness virus to wild and domestic ruminants and equids. Outbreaks of these viruses have caused economic damage within the European Union. The spatio-temporal distribution of biting midges is a key factor in identifying areas with the potential for disease spread. The aim of this study was to identify and map areas of neglectable adult activity for each month in an average year. Average monthly risk maps can be used as a tool when allocating resources for surveillance and control programs within Europe. Methods We modelled the occurrence of C. imicola and the Obsoletus and Pulicaris ensembles using existing entomological surveillance data from Spain, France, Germany, Switzerland, Austria, Denmark, Sweden, Norway and Poland. The monthly probability of each vector species and ensembles being present in Europe based on climatic and environmental input variables was estimated with the machine learning technique Random Forest. Subsequently, the monthly probability was classified into three classes: Absence, Presence and Uncertain status. These three classes are useful for mapping areas of no risk, areas of high-risk targeted for animal movement restrictions, and areas with an uncertain status that need active entomological surveillance to determine whether or not vectors are present. Results The distribution of Culicoides species ensembles were in agreement with their previously reported distribution in Europe. The Random Forest models were very accurate in predicting the probability of presence for C. imicola (mean AUC = 0.95), less accurate for the Obsoletus ensemble (mean AUC = 0.84), while the lowest accuracy was found for the Pulicaris ensemble (mean AUC = 0.71). The most important environmental variables in the models were related to temperature and precipitation for all three groups. Conclusions The duration ...

Background: Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) are vectors of bluetongue virus (BTV), African horse sickness virus and Schmallenberg virus (SBV). Outbreaks of both BTV and SBV have affected large parts of Europe. The spread of these diseases depends largely on vector distribution and abundance. The aim of this analysis was to identify and quantify major spatial patterns and temporal trends in the distribution and seasonal variation of observed Culicoides abundance in nine countries in Europe. Methods: We gathered existing Culicoides data from Spain, France, Germany, Switzerland, Austria, Denmark, Sweden, Norway and Poland. In total, 31,429 Culicoides trap collections were available from 904 ruminant farms across these countries between 2007 and 2013. Results: The Obsoletus ensemble was distributed widely in Europe and accounted for 83% of all 8,842,998 Culicoides specimens in the dataset, with the highest mean monthly abundance recorded in France, Germany and southern Norway. The Pulicaris ensemble accounted for only 12% of the specimens and had a relatively southerly and easterly spatial distribution compared to the Obsoletus ensemble. Culicoides imicola Kieffer was only found in Spain and the southernmost part of France. There was a clear spatial trend in the accumulated annual abundance from southern to northern Europe, with the Obsoletus ensemble steadily increasing from 4000 per year in southern Europe to 500,000 in Scandinavia. The Pulicaris ensemble showed a very different pattern, with an increase in the accumulated annual abundance from 1600 in Spain, peaking at 41,000 in northern Germany and then decreasing again toward northern latitudes. For the two species ensembles and C. imicola, the season began between January and April, with later start dates and increasingly shorter vector seasons at more northerly latitudes. Conclusion: We present the first maps of seasonal Culicoides abundance in large parts of Europe covering a gradient from southern Spain to northern Scandinavia. The identified temporal trends and spatial patterns are useful for planning the allocation of resources for international prevention and surveillance programmes in the European Union.

International audience ; Background: Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) are vectors of bluetongue virus (BTV), African horse sickness virus and Schmallenberg virus (SBV). Outbreaks of both BTV and SBV have affected large parts of Europe. The spread of these diseases depends largely on vector distribution and abundance. The aim of this analysis was to identify and quantify major spatial patterns and temporal trends in the distribution and seasonal variation of observed Culicoides abundance in nine countries in Europe. Methods: We gathered existing Culicoides data from Spain, France, Germany, Switzerland, Austria, Denmark, Sweden, Norway and Poland. In total, 31,429 Culicoides trap collections were available from 904 ruminant farms across these countries between 2007 and 2013. Results: The Obsoletus ensemble was distributed widely in Europe and accounted for 83% of all 8,842,998 Culicoides specimens in the dataset, with the highest mean monthly abundance recorded in France, Germany and southern Norway. The Pulicaris ensemble accounted for only 12% of the specimens and had a relatively southerly and easterly spatial distribution compared to the Obsoletus ensemble. Culicoides imicola Kieffer was only found in Spain and the southernmost part of France. There was a clear spatial trend in the accumulated annual abundance from southern to northern Europe, with the Obsoletus ensemble steadily increasing from 4000 per year in southern Europe to 500,000 in Scandinavia. The Pulicaris ensemble showed a very different pattern, with an increase in the accumulated annual abundance from 1600 in Spain, peaking at 41,000 in northern Germany and then decreasing again toward northern latitudes. For the two species ensembles and C. imicola, the season began between January and April, with later start dates and increasingly shorter vector seasons at more northerly latitudes. Conclusion: We present the first maps of seasonal Culicoides abundance in large parts of Europe covering a gradient from southern Spain to northern Scandinavia. The identified temporal trends and spatial patterns are useful for planning the allocation of resources for international prevention and surveillance programmes in the European Union.

Background: Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) are small hematophagous insects responsible for the transmission of bluetongue virus, Schmallenberg virus and African horse sickness virus to wild and domestic ruminants and equids. Outbreaks of these viruses have caused economic damage within the European Union. The spatio-temporal distribution of biting midges is a key factor in identifying areas with the potential for disease spread. The aim of this study was to identify and map areas of neglectable adult activity for each month in an average year. Average monthly risk maps can be used as a tool when allocating resources for surveillance and control programs within Europe. Methods : We modelled the occurrence of C. imicola and the Obsoletus and Pulicaris ensembles using existing entomological surveillance data from Spain, France, Germany, Switzerland, Austria, Denmark, Sweden, Norway and Poland. The monthly probability of each vector species and ensembles being present in Europe based on climatic and environmental input variables was estimated with the machine learning technique Random Forest. Subsequently, the monthly probability was classified into three classes: Absence, Presence and Uncertain status. These three classes are useful for mapping areas of no risk, areas of high-risk targeted for animal movement restrictions, and areas with an uncertain status that need active entomological surveillance to determine whether or not vectors are present. Results: The distribution of Culicoides species ensembles were in agreement with their previously reported distribution in Europe. The Random Forest models were very accurate in predicting the probability of presence for C. imicola (mean AUC = 0.95), less accurate for the Obsoletus ensemble (mean AUC = 0.84), while the lowest accuracy was found for the Pulicaris ensemble (mean AUC = 0.71). The most important environmental variables in the models were related to temperature and precipitation for all three groups. Conclusions: The duration periods with low or null adult activity can be derived from the associated monthly distribution maps, and it was also possible to identify and map areas with uncertain predictions. In the absence of ongoing vector surveillance, these maps can be used by veterinary authorities to classify areas as likely vector-free or as likely risk areas from southern Spain to northern Sweden with acceptable precision. The maps can also focus costly entomological surveillance to seasons and areas where the predictions and vector-free status remain uncertain.

Background: Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) are small hematophagous insects responsible for the transmission of bluetongue virus, Schmallenberg virus and African horse sickness virus to wild and domestic ruminants and equids. Outbreaks of these viruses have caused economic damage within the European Union. The spatio-temporal distribution of biting midges is a key factor in identifying areas with the potential for disease spread. The aim of this study was to identify and map areas of neglectable adult activity for each month in an average year. Average monthly risk maps can be used as a tool when allocating resources for surveillance and control programs within Europe. Methods: We modelled the occurrence of C. imicola and the Obsoletus and Pulicaris ensembles using existing entomological surveillance data from Spain, France, Germany, Switzerland, Austria, Denmark, Sweden, Norway and Poland. The monthly probability of each vector species and ensembles being present in Europe based on climatic and environmental input variables was estimated with the machine learning technique Random Forest. Subsequently, the monthly probability was classified into three classes: Absence, Presence and Uncertain status. These three classes are useful for mapping areas of no risk, areas of high-risk targeted for animal movement restrictions, and areas with an uncertain status that need active entomological surveillance to determine whether or not vectors are present. Results: The distribution of Culicoides species ensembles were in agreement with their previously reported distribution in Europe. The Random Forest models were very accurate in predicting the probability of presence for C. imicola (mean AUC = 0.95), less accurate for the Obsoletus ensemble (mean AUC = 0.84), while the lowest accuracy was found for the Pulicaris ensemble (mean AUC = 0.71). The most important environmental variables in the models were related to temperature and precipitation for all three groups. Conclusions: The duration periods with low or null adult activity can be derived from the associated monthly distribution maps, and it was also possible to identify and map areas with uncertain predictions. In the absence of ongoing vector surveillance, these maps can be used by veterinary authorities to classify areas as likely vector-free or as likely risk areas from southern Spain to northern Sweden with acceptable precision. The maps can also focus costly entomological surveillance to seasons and areas where the predictions and vector-free status remain uncertain.