Obituary - Professor Rolf Garms 1931 - 2021

Obituary - No abstract available

Vector Competence of the Invasive Mosquito Species Aedes koreicus for Arboviruses and Interference with a Novel Insect Specific Virus

The global spread of invasive mosquito species increases arbovirus infections. In addition to the invasive species Aedes albopictus and Aedes japonicus, Aedes koreicus has spread within Central Europe. Extensive information on its vector competence is missing. Ae. koreicus from Germany were investigated for their vector competence for chikungunya virus (CHIKV), Zika virus (ZIKV) and West Nile virus (WNV). Experiments were performed under different climate conditions (27 ± 5 °C; 24 ± 5 °C) for fourteen days. Ae. koreicus had the potential to transmit CHIKV and ZIKV but not WNV. Transmission was exclusively observed at the higher temperature, and transmission efficiency was rather low, at 4.6% (CHIKV) or 4.7% (ZIKV). Using a whole virome analysis, a novel mosquito-associated virus, designated Wiesbaden virus (WBDV), was identified in Ae. koreicus. Linking the WBDV infection status of single specimens to their transmission capability for the arboviruses revealed no influence on ZIKV transmission. In contrast, a coinfection of WBDV and CHIKV likely has a boost effect on CHIKV transmission. Due to its current distribution, the risk of arbovirus transmission by Ae. koreicus in Europe is rather low but might gain importance, especially in regions with higher temperatures. The impact of WBDV on arbovirus transmission should be analyzed in more detail

Evidence for West Nile Virus and Usutu Virus Infections in Wild and Resident Birds in Germany, 2017 and 2018

Wild birds play an important role as reservoir hosts and vectors for zoonotic arboviruses and foster their spread. Usutu virus (USUV) has been circulating endemically in Germany since 2011, while West Nile virus (WNV) was first diagnosed in several bird species and horses in 2018. In 2017 and 2018, we screened 1709 live wild and zoo birds with real-time polymerase chain reaction and serological assays. Moreover, organ samples from bird carcasses submitted in 2017 were investigated. Overall, 57 blood samples of the live birds (2017 and 2018), and 100 organ samples of dead birds (2017) were positive for USUV-RNA, while no WNV-RNA-positive sample was found. Phylogenetic analysis revealed the first detection of USUV lineage Europe 2 in Germany and the spread of USUV lineages Europe 3 and Africa 3 towards Northern Germany. USUV antibody prevalence rates were high in Eastern Germany in both years. On the contrary, in Northern Germany, high seroprevalence rates were first detected in 2018, with the first emergence of USUV in this region. Interestingly, high WNV-specific neutralizing antibody titers were observed in resident and short-distance migratory birds in Eastern Germany in 2018, indicating the first signs of a local WNV circulation

Vector Competence of Northern European Culex pipiens Biotype pipiens and Culex torrentium to West Nile Virus and Sindbis Virus

The West Nile Virus (WNV) and Sindbis virus (SINV) are avian-hosted mosquito-borne zoonotic viruses that co-circulate in some geographical areas and share vector species such as Culex pipiens and Culex torrentium. These are widespread in Europe, including northern parts and Finland, where SINV is endemic, but WNV is currently not. As WNV is spreading northwards in Europe, we wanted to assess the experimental vector competence of Finnish Culex pipiens and Culex torrentium mosquitoes to WNV and SINV in different temperature profiles. Both mosquito species were found susceptible to both viruses and got infected via infectious blood meal at a mean temperature of 18 °C. WNV-positive saliva was detected at a mean temperature of 24 °C, whereas SINV-positive saliva was detected already at a mean temperature of 18 °C. Cx. torrentium was found to be a more efficient vector for WNV and SINV over Cx. pipiens. Overall, the results were in line with the previous studies performed with more southern vector populations. The current climate does not seem optimal for WNV circulation in Finland, but temporary summertime transmission could occur in the future if all other essential factors are in place. More field data would be needed for monitoring and understanding the northward spreading of WNV in Europe

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

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

AIMSurv: First pan-European harmonized surveillance of Aedes invasive mosquito species of relevance for human vector-borne diseases

Human and animal vector-borne diseases, particularly mosquito-borne diseases, are emerging or re-emerging worldwide. Six Aedes invasive mosquito (AIM) species were introduced to Europe since the 1970s: Aedes aegypti, Ae. albopictus, Ae. japonicus, Ae. koreicus, Ae. atropalpus and Ae. triseriatus. Here, we report the results of AIMSurv2020, the first pan-European surveillance effort for AIMs. Implemented by 42 volunteer teams from 24 countries. And presented in the form of a dataset named “AIMSurv Aedes Invasive Mosquito species harmonized surveillance in Europe. AIM-COST Action. Project ID: CA17108”. AIMSurv2020 harmonizes field surveillance methodologies for sampling different AIMs life stages, frequency and minimum length of sampling period, and data reporting. Data include minimum requirements for sample types and recommended requirements for those teams with more resources. Data are published as a Darwin Core archive in the Global Biodiversity Information Facility- Spain, comprising a core file with 19,130 records (EventID) and an occurrences file with 19,743 records (OccurrenceID). AIM species recorded in AIMSurv2020 were Ae. albopictus, Ae. japonicus and Ae. koreicus, as well as native mosquito species

Evaluating the risk for Usutu virus circulation in Europe : comparison of environmental niche models and epidemiological models

Abstract Background Usutu virus (USUV) is a mosquito-borne flavivirus, reported in many countries of Africa and Europe, with an increasing spatial distribution and host range. Recent outbreaks leading to regional declines of European common blackbird (Turdus merula) populations and a rising number of human cases emphasize the need for increased awareness and spatial risk assessment. Methods Modelling approaches in ecology and epidemiology differ substantially in their algorithms, potentially resulting in diverging model outputs. Therefore, we implemented a parallel approach incorporating two commonly applied modelling techniques: (1) Maxent, a correlation-based environmental niche model and (2) a mechanistic epidemiological susceptible-exposed-infected-removed (SEIR) model. Across Europe, surveillance data of USUV-positive birds from 2003 to 2016 was acquired to train the environmental niche model and to serve as test cases for the SEIR model. The SEIR model is mainly driven by daily mean temperature and calculates the basic reproduction number R0. The environmental niche model was run with long-term bio-climatic variables derived from the same source in order to estimate climatic suitability. Results Large areas across Europe are currently suitable for USUV transmission. Both models show patterns of high risk for USUV in parts of France, in the Pannonian Basin as well as northern Italy. The environmental niche model depicts the current situation better, but with USUV still being in an invasive stage there is a chance for under-estimation of risk. Areas where transmission occurred are mostly predicted correctly by the SEIR model, but it mostly fails to resolve the temporal dynamics of USUV events. High R0 values predicted by the SEIR model in areas without evidence for real-life transmission suggest that it may tend towards over-estimation of risk. Conclusions The results from our parallel-model approach highlight that relying on a single model for assessing vector-borne disease risk may lead to incomplete conclusions. Utilizing different modelling approaches is thus crucial for risk-assessment of under-studied emerging pathogens like USUV