Molecular detection of Babesia spp. in dogs in Germany (2007-2020) and identification of potential risk factors for infection.

BACKGROUND: In Europe, canine babesiosis is most frequently caused by Babesia canis and Babesia vogeli, and occasionally by Babesia gibsoni.. In Germany, B. canis is recognized as endemic. The aims of this study were to assess how often Babesia spp. infections were diagnosed in a commercial laboratory in samples from dogs from Germany, and to evaluate potential risk factors for infection. METHODS: The database of the LABOKLIN laboratory was screened for Babesia spp.-positive polymerase chain reaction (PCR) tests for dogs for the period January 2007-December 2020. Sequencing was performed for positive tests from 2018 and 2019. Binary logistic regression analysis was performed to determine the effects of sex, season, and year of testing. Questionnaires were sent to the submitting veterinarians to obtain information on travel abroad, tick infestation, and ectoparasite prophylaxis of the respective dogs. Fisher's exact test was used to calculate statistical significance and P < 0.05 was considered statistically significant. RESULTS: In total, 659 out of 20,914 dogs (3.2%) tested positive for Babesia spp. by PCR. Of 172 sequenced samples, B. canis was identified in 156, B. vogeli in nine, B. gibsoni in five, and B. vulpes in two. Season had a statistically significant impact on test results when summer/winter (1.6% tested positive) was compared to spring/autumn (4.7%), with peaks in April (5.2%) and October (7.4%) [P < 0.001, odds ratio (OR) = 3.16]. Sex (male 3.5%, female 2.8%; P = 0.012, OR = 1.49) and age (< 7 years old 4.0%, ≥ 7 years old 2.3%; P < 0.001, OR = 1.76) of the tested dogs also had a statistically significant effect. A statistically significant impact was demonstrated for observed tick attachment (P < 0.001, OR = 7.62) and lack of ectoparasite prophylaxis (P = 0.001, OR = 3.03). The frequency of positive Babesia spp. tests did not significantly differ between the 659 dogs that had never left Germany and the 1506 dogs with known stays abroad (P = 0.088). CONCLUSIONS: The possibility of canine infection with B. canis needs to be especially taken into consideration in spring and autumn in Germany as the activity of the tick Dermacentor reticulatus, a potential vector for canine babesiosis, is highest in these seasons. Travel and importation of dogs are considered major factors associated with canine babesiosis in Germany. However, autochthonous Babesia spp. infections also occur in a considerable number of dogs in Germany.

VectorNet: collaborative mapping of arthropod disease vectors in Europe and surrounding areas since 2010.

BackgroundArthropod vectors such as ticks, mosquitoes, sandflies and biting midges are of public and veterinary health significance because of the pathogens they can transmit. Understanding their distributions is a key means of assessing risk. VectorNet maps their distribution in the EU and surrounding areas.AimWe aim to describe the methodology underlying VectorNet maps, encourage standardisation and evaluate output.Methods: Vector distribution and surveillance activity data have been collected since 2010 from a combination of literature searches, field-survey data by entomologist volunteers via a network facilitated for each participating country and expert validation. Data were collated by VectorNet members and extensively validated during data entry and mapping processes.ResultsAs of 2021, the VectorNet archive consisted of ca 475,000 records relating to > 330 species. Maps for 42 species are routinely produced online at subnational administrative unit resolution. On VectorNet maps, there are relatively few areas where surveillance has been recorded but there are no distribution data. Comparison with other continental databases, namely the Global Biodiversity Information Facility and VectorBase show that VectorNet has 5-10 times as many records overall, although three species are better represented in the other databases. In addition, VectorNet maps show where species are absent. VectorNet's impact as assessed by citations (ca 60 per year) and web statistics (58,000 views) is substantial and its maps are widely used as reference material by professionals and the public.ConclusionVectorNet maps are the pre-eminent source of rigorously validated arthropod vector maps for Europe and its surrounding areas.

Molecular and Serological Detection of Anaplasma phagocytophilum in Dogs from Germany (2008-2020).

Anaplasma phagocytophilum is an obligate intracellular bacterium that causes granulocytic anaplasmosis in domestic animals, wildlife, and humans and is primarily transmitted by ticks of the Ixodes persulcatus complex. This retrospective study aims to determine the percentages of dogs that tested positive for A. phagocytophilum in Germany. It included the results of direct (polymerase chain reaction [PCR]) and indirect (immunofluorescence antibody test [IFAT], antibody-enzyme-linked immunosorbent assay [ELISA]) detection methods performed in the laboratory LABOKLIN on canine samples provided by German veterinarians from 2008 to 2020. Out of a total of 27,368 dogs tested by PCR, 1332 (4.9%) tested positive, while 24,720 (27.4%) of the 90,376 dogs tested by IFAT/ELISA had positive serology. High rates of positive PCR results were observed in months with known peaks in vector activity, showing that the dynamics of A. phagocytophilum infections in dogs in Germany are consistent with vector activity. In dogs with a positive PCR result, peaks in serology could be observed four weeks after initial testing. Male and senior dogs had higher rates of positive serology. A possible impact of environmental factors such as changes in climate should be investigated further. Overall, the upward trend in positive test results over the years indicates that canine granulocytic anaplasmosis will continue to become increasingly important for veterinary medicine.

Detection of Anaplasma phagocytophilum in horses from Germany by molecular and serological testing (2008-2021).

BACKGROUND: Equine granulocytic anaplasmosis (EGA) is a tick-borne disease caused by Anaplasma (A.) phagocytophilum. In Germany, this pathogen is transmitted primarily by Ixodes ricinus. There is limited knowledge about its prevalence in horses in Germany. The aim of this retrospective study was to analyze the results of serological and molecular testing for A. phagocytophilum in horses which were done in a commercial laboratory in Germany over fourteen years. Additionally, risk factors were evaluated, and hematological abnormalities were addressed in horses with positive PCR results. METHODS: This retrospective study examined results of direct (Polymerase chain reaction [PCR]) and indirect (immunofluorescence antibody test [IFAT]) detection methods for A. phagocytophilum in horses on samples provided by German veterinarians and processed by the commercial laboratory LABOKLIN from 2008 to 2021. In horses with positive test results, a Complete Blood Count (CBC) and Serum Amyloid A (SAA) were also analyzed where possible. RESULTS: In total, 1217/4834 horses tested positive (PCR: 190/1246 horses, 15.2%; IFAT: 1036/3849 horses, 26.9%). Seasonality and location, as classified by federal state, had a statistically significant impact on PCR results (P < 0.001 for both). In horses with positive PCR results, hematological abnormalities were detected in 112/118 horses (95%), with thrombocytopenia (86%) and anemia (52%) representing the most common findings. The remaining 6/118 horses (5%) showed no hematological abnormalities on CBC. SAA was measured in 35 horses with positive PCR results, which exclusively showed marked elevation. CONCLUSIONS: The seasonality of A. phagocytophilum infections confirmed by PCR testing was consistent with known peaks in vector activity in Germany. The high rate of horses with positive PCR results when compared to dogs and cats may be due to a lack of ectoparasite prophylaxis. Infections with A. phagocytophilum should be considered as a differential diagnosis in horses with cytopenia on CBC and SAA elevation, especially in the summer and after any possible tick exposure.

Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland.

BACKGROUND: Ticks are responsible for transmitting several notable pathogens worldwide. Finland lies in a zone where two human-biting tick species co-occur: Ixodes ricinus and Ixodes persulcatus. Tick densities have increased in boreal regions worldwide during past decades, and tick-borne pathogens have been identified as one of the major threats to public health in the face of climate change. METHODS: We used species distribution modelling techniques to predict the distributions of I. ricinus and I. persulcatus, using aggregated historical data from 2014 to 2020 and new tick occurrence data from 2021. By aiming to fill the gaps in tick occurrence data, we created a new sampling strategy across Finland. We also screened for tick-borne encephalitis virus (TBEV) and Borrelia from the newly collected ticks. Climate, land use and vegetation data, and population densities of the tick hosts were used in various combinations on four data sets to estimate tick species' distributions across mainland Finland with a 1-km resolution. RESULTS: In the 2021 survey, 89 new locations were sampled of which 25 new presences and 63 absences were found for I. ricinus and one new presence and 88 absences for I. persulcatus. A total of 502 ticks were collected and analysed; no ticks were positive for TBEV, while 56 (47%) of the 120 pools, including adult, nymph, and larva pools, were positive for Borrelia (minimum infection rate 11.2%, respectively). Our prediction results demonstrate that two combined predictor data sets based on ensemble mean models yielded the highest predictive accuracy for both I. ricinus (AUC = 0.91, 0.94) and I. persulcatus (AUC = 0.93, 0.96). The suitable habitats for I. ricinus were determined by higher relative humidity, air temperature, precipitation sum, and middle-infrared reflectance levels and higher densities of white-tailed deer, European hare, and red fox. For I. persulcatus, locations with greater precipitation and air temperature and higher white-tailed deer, roe deer, and mountain hare densities were associated with higher occurrence probabilities. Suitable habitats for I. ricinus ranged from southern Finland up to Central Ostrobothnia and North Karelia, excluding areas in Ostrobothnia and Pirkanmaa. For I. persulcatus, suitable areas were located along the western coast from Ostrobothnia to southern Lapland, in North Karelia, North Savo, Kainuu, and areas in Pirkanmaa and Päijät-Häme. CONCLUSIONS: This is the first study conducted in Finland that estimates potential tick species distributions using environmental and host data. Our results can be utilized in vector control strategies, as supporting material in recommendations issued by public health authorities, and as predictor data for modelling the risk for tick-borne diseases.

VectorNet: Putting Vectors on the Map.

Public and animal health authorities face many challenges in surveillance and control of vector-borne diseases. Those challenges are principally due to the multitude of interactions between vertebrate hosts, pathogens, and vectors in continuously changing environments. VectorNet, a joint project of the European Food Safety Authority (EFSA) and the European Centre for Disease Prevention and Control (ECDC) facilitates risk assessments of VBD threats through the collection, mapping and sharing of distribution data for ticks, mosquitoes, sand flies, and biting midges that are vectors of pathogens of importance to animal and/or human health in Europe. We describe the development and maintenance of this One Health network that celebrated its 10th anniversary in 2020 and the value of its most tangible outputs, the vector distribution maps, that are freely available online and its raw data on request. VectorNet encourages usage of these maps by health professionals and participation, sharing and usage of the raw data by the network and other experts in the science community. For the latter, a more complete technical description of the mapping procedure will be submitted elsewhere.

Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data.

Pogosta disease is a mosquito-borne infection, caused by Sindbis virus (SINV), which causes epidemics of febrile rash and arthritis in Northern Europe and South Africa. Resident grouse and migratory birds play a significant role as amplifying hosts and various mosquito species, including Aedes cinereus, Culex pipiens, Cx. torrentium and Culiseta morsitans are documented vectors. As specific treatments are not available for SINV infections, and joint symptoms may persist, the public health burden is considerable in endemic areas. To predict the environmental suitability for SINV infections in Finland, we applied a suite of geospatial and statistical modeling techniques to disease occurrence data. Using an ensemble approach, we first produced environmental suitability maps for potential SINV vectors in Finland. These suitability maps were then combined with grouse densities and environmental data to identify the influential determinants for SINV infections and to predict the risk of Pogosta disease in Finnish municipalities. Our predictions suggest that both the environmental suitability for vectors and the high risk of Pogosta disease are focused in geographically restricted areas. This provides evidence that the presence of both SINV vector species and grouse densities can predict the occurrence of the disease. The results support material for public-health officials when determining area-specific recommendations and deliver information to health care personnel to raise awareness of the disease among physicians.

Seasonality and timing of peak abundance of Aedes albopictus in Europe: Implications to public and animal health.

Aedes albopictus is a known vector of dengue and chikungunya. Understanding the population dynamics characteristics of vector species is of pivotal importance to optimise surveillance and control activities, to estimate risk for pathogen-transmission, and thus to enhance support of public health decisions. In this paper we used a seasonal activity model to simulate the start (spring hatching) and end (autumn diapause) of the vector season. In parallel, the peak abundance of the species was assessed using both VectorNet field survey data complemented with field studies obtained from literature across the Mediterranean Basin. Our results suggest that spring hatching of eggs in the current distribution area can start at the beginning of March in southern Europe and in April in western Europe. In northern Europe, where the species is not (yet) present, spring hatching would occur from late April to late May. Aedes albopictus can remain active up to 41 weeks in southern Europe whilst the climatic conditions in northern Europe are limiting its potential activity to a maximum of 23 weeks. The peak of egg density is found during summer months from end of July until end of September. During these two months the climatic conditions for species development are optimal, which implies a higher risk for arbovirus transmission by Ae. albopictus and occurrence of epidemics.

Constraints of using historical data for modelling the spatial distribution of helminth parasites in ruminants.

Dicrocoelium dendriticum is a trematode that infects ruminant livestock and requires two different intermediate hosts to complete its lifecycle. Modelling the spatial distribution of this parasite can help to improve its management in higher risk regions. The aim of this research was to assess the constraints of using historical data sets when modelling the spatial distribution of helminth parasites in ruminants. A parasitological data set provided by CREMOPAR (Napoli, Italy) and covering most of Italy was used in this paper. A baseline model (Random Forest, VECMAP®) using the entire data set was first used to determine the minimal number of data points needed to build a stable model. Then, annual distribution models were computed and compared with the baseline model. The best prediction rate and statistical output were obtained for 2012 and the worst for 2016, even though the sample size of the former was significantly smaller than the latter. We discuss how this may be explained by the fact that in 2012, the samples were more evenly geographically distributed, whilst in 2016 most of the data were strongly clustered. It is concluded that the spatial distribution of the input data appears to be more important than the actual sample size when computing species distribution models. This is often a major issue when using historical data to develop spatial models. Such data sets often include sampling biases and large geographical gaps. If this bias is not corrected, the spatial distribution model outputs may display the sampling effort rather than the real species distribution.

TITLE: Contraintes liées à l'utilisation de données historiques pour la modélisation de la distribution spatiale des helminthes parasites chez les ruminants. ABSTRACT: Dicrocoelium dendriticum est un trématode qui infecte les ruminants et nécessite deux hôtes intermédiaires différents pour terminer son cycle de vie. La modélisation de la distribution spatiale de ce parasite peut aider à améliorer sa gestion dans les régions à haut risque. L'objectif de cette recherche était d'évaluer les contraintes liées à l'utilisation d'ensembles de données historiques lors de la modélisation de la distribution spatiale des helminthes parasites chez les ruminants. Un ensemble de données parasitologiques fourni par CREMOPAR (Naples, Italie) et couvrant la majeure partie de l'Italie a été utilisé dans cet article. Un modèle de base (Random Forest, VECMAP®) utilisant l'ensemble des données a d'abord été utilisé pour déterminer le nombre minimal de points de données nécessaires pour construire un modèle stable. Ensuite, des modèles de distribution annuelle ont été calculés et comparés au modèle de référence. Le meilleur taux de prédiction et le meilleur résultat statistique ont été obtenus pour 2012 et le plus mauvais pour 2016, malgré le fait que la taille de l'échantillon du premier était nettement plus petite que celle du second. Nous discutons comment cela peut s'expliquer par le fait qu'en 2012, les échantillons étaient plus uniformément répartis géographiquement, alors qu'en 2016, la plupart des données étaient fortement regroupées. On conclut que la distribution spatiale des données d'entrée semble être plus importante que la taille réelle de l'échantillon lors du calcul des modèles de distribution des espèces. C'est souvent un problème majeur pour développer des modèles spatiaux quand on utilise des données historiques. Ces ensembles de données comportent souvent des biais d'échantillonnage et de grandes lacunes géographiques. Si ce biais n'est pas corrigé, les résultats du modèle de distribution spatiale peuvent représenter l'effort d'échantillonnage plutôt que la distribution réelle des espèces.

Publisher Correction: Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus.

This Article was mistakenly not made Open Access when originally published; this has now been amended, and information about the Creative Commons Attribution 4.0 International License has been added into the 'Additional information' section.

Publisher Correction: Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus.

In the version of this Article originally published, the affiliation for author Catherine Linard was incorrectly stated as '6Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK'. The correct affiliation is '9Spatial Epidemiology Lab (SpELL), Universite Libre de Bruxelles, Brussels, Belgium'. The affiliation for author Hongjie Yu was also incorrectly stated as '11Department of Statistics, Harvard University, Cambridge, MA, USA'. The correct affiliation is '15School of Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China'. This has now been amended in all versions of the Article.

Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus.

The global population at risk from mosquito-borne diseases-including dengue, yellow fever, chikungunya and Zika-is expanding in concert with changes in the distribution of two key vectors: Aedes aegypti and Aedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction. We find that the spread of Ae. aegypti is characterized by long distance importations, while Ae. albopictus has expanded more along the fringes of its distribution. We describe these processes and predict the future distributions of both species in response to accelerating urbanization, connectivity and climate change. Global surveillance and control efforts that aim to mitigate the spread of chikungunya, dengue, yellow fever and Zika viruses must consider the so far unabated spread of these mosquitos. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally.