The prevalence of atypical scrapie in sheep from positive flocks is not higher than in the general sheep population in 11 European countries

Background: During the last decade, active surveillance for transmissible spongiform encephalopathies in small ruminants has been intensive in Europe. In many countries this has led to the detection of cases of atypical scrapie which, unlike classical scrapie, might not be contagious. EU legislation requires, that following detection of a scrapie case, control measures including further testing take place in affected flocks, including the culling of genotype susceptible to classical scrapie. This might result in the detection of additional cases. The aim of this study was to investigate the occurrence of additional cases in flocks affected by atypical scrapie using surveillance data collected in Europe in order to ascertain whether atypical scrapie, is contagious. Results: Questionnaires were used to collect, at national level, the results of active surveillance and testing associated with flock outbreaks in 12 European countries. The mean prevalence of atypical scrapie was 5.5 (5.0-6.0) cases per ten thousand in abattoir surveillance and 8.1 (7.3-9.0) cases per ten thousand in fallen stock. By using meta-analysis, on 11 out of the 12 countries, we found that the probability of detecting additional cases of atypical scrapie in positive flocks was similar to the probability observed in animals slaughtered for human consumption (odds ratio, OR = 1.07, CI95%: 0.70-1.63) or among fallen stock (OR = 0.78, CI95%: 0.51-1.2). In contrast, when comparing the two scrapie types, the probability of detecting additional cases in classical scrapie positive flocks was significantly higher than the probability of detecting additional cases in atypical scrapie positive flocks (OR = 32.4, CI95%: 20.7-50.7). Conclusions: These results suggest that atypical scrapie is not contagious or has a very low transmissibility under natural conditions compared with classical scrapie. Furthermore this study stressed the importance of standardised data collection to make good use of the analyses undertaken by European countries in their efforts to control atypical and classical scrapie

Existence and Quality of Data on Control Programs for EU Non-regulated Cattle Diseases: Consequences for Estimation and Comparison of the Probability of Freedom From Infection

Some European countries have successfully implemented country-specific control programs (CPs) for infectious cattle diseases that are not regulated or are regulated only to a limited extent at the European Union (EU) level. Examples of such diseases include bovine viral diarrhea (BVD), infectious bovine rhinotracheitis (IBR), and Johne's disease (JD). The CPs vary between countries in the design and quality of collected data as well as methods used to detect infection and estimate prevalence or probability of freedom from infection. Differences in disease status between countries and non-standardized approaches to assess freedom from infection pose a risk for countries with CPs for non-regulated diseases as infected animals may influence the progress of the disease control or eradication program. The implementation of output-based standards allows estimation and comparison of the probability of freedom for non-regulated cattle diseases in European countries. The aim of the current study was to assess the existence and quality of data that could be used for estimating freedom from infection in European countries. The online data collection tool was sent to 32 countries participating in the SOUND control COST Action and was completed by 24 countries. Data on cattle demographics and data from CPs of IBR and BVD exist in more than 50% of the response countries. However, data describing risk factors and CP of JD was reported as existing in < 25% of the countries. The overall quality of data in the sections on demographics and CPs of IBR and BVD were evaluated as "good ", but risk factors and JD data were mostly evaluated as "fair. " Data quality was considered less good mainly due to two quality criteria: accessibility and accuracy. The results of this study show that the quantity and quality of data about cattle populations and CPs are relatively similar in many surveyed countries. The outcome of this work provides an overview of the current situation in the European countries regarding data on EU non-regulated cattle diseases and will further assist in the development and implementation of output-based standards

Modelling the monthly abundance of Culicoides biting midges in nine European countries using Random Forests machine learning

Background: Culicoides biting midges transmit viruses resulting in disease in ruminants and equids such as bluetongue, Schmallenberg disease and African horse sickness. In the past decades, these diseases have led to important economic losses for farmers in Europe. Vector abundance is a key factor in determining the risk of vector-borne disease spread and it is, therefore, important to predict the abundance of Culicoides species involved in the transmission of these pathogens. The objectives of this study were to model and map the monthly abundances of Culicoides in Europe. Methods: We obtained entomological data from 904 farms in nine European countries (Spain, France, Germany, Switzerland, Austria, Poland, Denmark, Sweden and Norway) from 2007 to 2013. Using environmental and climatic predictors from satellite imagery and the machine learning technique Random Forests, we predicted the monthly average abundance at a 1 km2 resolution. We used independent test sets for validation and to assess model performance. Results: The predictive power of the resulting models varied according to month and the Culicoides species/ensembles predicted. Model performance was lower for winter months. Performance was higher for the Obsoletus ensemble, followed by the Pulicaris ensemble, while the model for Culicoides imicola showed a poor performance. Distribution and abundance patterns corresponded well with the known distributions in Europe. The Random Forests model approach was able to distinguish differences in abundance between countries but was not able to predict vector abundance at individual farm level. Conclusions: The models and maps presented here represent an initial attempt to capture large scale geographical and temporal variations in Culicoides abundance. The models are a first step towards producing abundance inputs for R0 modelling of Culicoides-borne infections at a continental scale

The Plasmodium Export Element Revisited

We performed a bioinformatical analysis of protein export elements (PEXEL) in the putative proteome of the malaria parasite Plasmodium falciparum. A protein family-specific conservation of physicochemical residue profiles was found for PEXEL-flanking sequence regions. We demonstrate that the family members can be clustered based on the flanking regions only and display characteristic hydrophobicity patterns. This raises the possibility that the flanking regions may contain additional information for a family-specific role of PEXEL. We further show that signal peptide cleavage results in a positional alignment of PEXEL from both proteins with, and without, a signal peptide

Monthly variation in the probability of presence of adult Culicoides populations in nine European countries and the implications for targeted surveillance

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

Norwegian farmers' vigilance in reporting sheep showing scrapie-associated signs

<p>Abstract</p> <p>Background</p> <p>Scrapie is a chronic neurodegenerative disease affecting small ruminants and belongs to the transmissible spongiform encephalopathies. Scrapie is considered a serious animal disease and it has been notifiable in Norway since 1965. The clinical signs of scrapie might be vague and the farmers, if familiar with the signs of scrapie, are often in the best position for detecting scrapie suspects. In 2002, an anonymous questionnaire survey was conducted in order to assess Norwegian sheep farmers' vigilance of scrapie.</p> <p>Results</p> <p>Although the potential detection of a scrapie-positive animal would lead to the destruction of the sheep flock concerned, almost all the farmers (97 %) expressed their willingness to report scrapie suspects. This was most certainly dependent on the Government taking the economic responsibility for the control programme as nearly all the farmers responded that this was an important condition. Listeriosis is relatively common disease in Norwegian sheep and a differential diagnosis for scrapie. In a multinomial logistic regression the reporting behaviour for non-recovering listeriosis cases, used as a measurement of willingness to report scrapie, was examined. The reporting of non-recovering listeriosis cases increased as the knowledge of scrapie-associated signs increased, and the reporting behaviour was dependent on both economic and non-economic values.</p> <p>Conclusion</p> <p>The results indicate that in 2002 almost all sheep farmers showed willingness to report any scrapie suspects. Nevertheless there is an underreporting of scrapie suspects and the farmers' awareness and hence their vigilance of scrapie could be improved. Furthermore, the results suggest that to ensure the farmers' compliance to control programmes for serious infectious diseases, the farmers' concerns of non-economic as well as economic values should be considered.</p