Suchergebnisse

Rift Valley fever (RVF) is a vector-borne disease transmitted by a broad spectrum of mosquito species, especially Aedes and Culex genus, to animals (domestic and wild ruminants and camels) and humans. Rift Valley fever is endemic in sub-Saharan Africa and in the Arabian Peninsula, with periodic epidemics characterised by 5–15 years of inter-epizootic periods. In the last two decades, RVF was notified in new African regions (e.g. Sahel), RVF epidemics occurred more frequently and low-level enzootic virus circulation has been demonstrated in livestock in various areas. Recent outbreaks in a French overseas department and some seropositive cases detected in Turkey, Tunisia and Libya raised the attention of the EU for a possible incursion into neighbouring countries. The movement of live animals is the most important pathway for RVF spread from the African endemic areas to North Africa and the Middle East. The movement of infected animals and infected vectors when shipped by flights, containers or road transport is considered as other plausible pathways of introduction into Europe. The overall risk of introduction of RVF into EU through the movement of infected animals is very low in all the EU regions and in all MSs (less than one epidemic every 500 years), given the strict EU animal import policy. The same level of risk of introduction in all the EU regions was estimated also considering the movement of infected vectors, with the highest level for Belgium, Greece, Malta, the Netherlands (one epidemic every 228–700 years), mainly linked to the number of connections by air and sea transports with African RVF infected countries. Although the EU territory does not seem to be directly exposed to an imminent risk of RVFV introduction, the risk of further spread into countries neighbouring the EU and the risks of possible introduction of infected vectors, suggest that EU authorities need to strengthen their surveillance and response capacities, as well as the collaboration with North African and Middle Eastern countries.

Rift Valley fever (RVF) is a vector‐borne disease transmitted by a broad spectrum of mosquito species, especially Aedes and Culex genus, to animals (domestic and wild ruminants and camels) and humans. Rift Valley fever is endemic in sub‐Saharan Africa and in the Arabian Peninsula, with periodic epidemics characterised by 5–15 years of inter‐epizootic periods. In the last two decades, RVF was notified in new African regions (e.g. Sahel), RVF epidemics occurred more frequently and low‐level enzootic virus circulation has been demonstrated in livestock in various areas. Recent outbreaks in a French overseas department and some seropositive cases detected in Turkey, Tunisia and Libya raised the attention of the EU for a possible incursion into neighbouring countries. The movement of live animals is the most important pathway for RVF spread from the African endemic areas to North Africa and the Middle East. The movement of infected animals and infected vectors when shipped by flights, containers or road transport is considered as other plausible pathways of introduction into Europe. The overall risk of introduction of RVF into EU through the movement of infected animals is very low in all the EU regions and in all MSs (less than one epidemic every 500 years), given the strict EU animal import policy. The same level of risk of introduction in all the EU regions was estimated also considering the movement of infected vectors, with the highest level for Belgium, Greece, Malta, the Netherlands (one epidemic every 228–700 years), mainly linked to the number of connections by air and sea transports with African RVF infected countries. Although the EU territory does not seem to be directly exposed to an imminent risk of RVFV introduction, the risk of further spread into countries neighbouring the EU and the risks of possible introduction of infected vectors, suggest that EU authorities need to strengthen their surveillance and response capacities, as well as the collaboration with North African and Middle Eastern countries.

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 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.