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Incidence of tick-borne encephalitis (TBE) has increased during the last years in Scandinavia, but the underlying mechanism is not understood. TBE human case data reported between 2010 and 2021 were aggregated into postal codes within orebro County, south-central Sweden, along with tick abundance and environmental data to analyse spatial patterns and identify drivers of TBE. We identified a substantial and continuing increase of TBE incidence in orebro County during the study period. Spatial cluster analyses showed significant hotspots (higher number of cases than expected) in the southern and northern parts of orebro County, whereas a cold spot (lower number of cases than expected) was found in the central part comprising orebro municipality. Generalised linear models showed that the risk of acquiring TBE increased by 12.5% and 72.3% for every percent increase in relative humidity and proportion of wetland forest, respectively, whereas the risk decreased by 52.8% for every degree Celsius increase in annual temperature range. However, models had relatively low goodness of fit (R-2 < 0.27). Results suggest that TBE in orebro County is spatially clustered, however variables used in this study, i.e., climatic variables, forest cover, water, tick abundance, sheep as indicator species, alone do not explain this pattern., Funding Agencies|Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS) [2016-01400]; Knowledge Foundation [20190091, 20200063]; European Union through the European Regional Development Fund; Interreg North Sea Region Programme 2014-2020 as part of the NorthTick project; Medical Research Council of Southeast Sweden (FORSS) [38-2-7-19]; Division of Laboratory Medicine; Stiftelsen Marie-Claire Cronstedts minne; Swedish University of Agricultural Sciences; Region Joenkoeping County; Region OErebro; [931010]

Ixodes ricinus ticks are Scandinavia's main vector for tick-borne encephalitis virus (TBEV), which infects many people annually. The aims of the present study were (i) to obtain information on the TBEV prevalence in host-seeking I. ricinus collected within the Øresund-Kattegat-Skagerrak (ØKS) region, which lies in southern Norway, southern Sweden and Denmark; (ii) to analyse whether there are potential spatial patterns in the TBEV prevalence; and (iii) to understand the relationship between TBEV prevalence and meteorological factors in southern Scandinavia. Tick nymphs were collected in 2016, in southern Scandinavia, and screened for TBEV, using pools of 10 nymphs, with RT real-time PCR, and positive samples were confirmed with pyrosequencing. Spatial autocorrelation and cluster analysis was performed with Global Moran's I and SatScan to test for spatial patterns and potential local clusters of the TBEV pool prevalence at each of the 50 sites. A climatic analysis was made to correlate parameters such as minimum, mean and maximum temperature, relative humidity and saturation deficit with TBEV pool prevalence. The climatic data were acquired from the nearest meteorological stations for 2015 and 2016. This study confirms the presence of TBEV in 12 out of 30 locations in Denmark, where six were from Jutland, three from Zealand and two from Bornholm and Falster counties. In total, five out of nine sites were positive from southern Sweden. TBEV prevalence of 0.7%, 0.5% and 0.5%, in nymphs, was found at three sites along the Oslofjord (two sites) and northern Skåne region (one site), indicating a potential concern for public health. We report an overall estimated TBEV prevalence of 0.1% in questing I. ricinus nymphs in southern Scandinavia with a region-specific prevalence of 0.1% in Denmark, 0.2% in southern Sweden and 0.1% in southeastern Norway. No evidence of a spatial pattern or local clusters was found in the study region. We found a strong correlation between TBE

Cloth-dragging is the most widely-used method for collecting and counting ticks, but there are few studies of its reliability. By using cloth-dragging, we applied a replicated line transects survey method, in two areas in Sweden with different Ixodes ricinus tick-densities (low at Grimso and high at Bogesund) to evaluate developmental stage specific repeatability, agreement and precision in estimates of tick abundance. Repeatability was expressed as the Intraclass Correlation Coefficient (ICC), agreement with the Total Deviation Index (TDI) and precision by the coefficient of variation (CV) for a given dragging distance. Repeatability (ICC) and agreement (TDI) were higher for the most abundant instar (nymphs) and in the area of higher abundance. At Bogesund tick counts were higher than at Grimso and so also repeatability, with fair to substantial ICC estimates between 0.22 and 0.75, and TDI ranged between 1 and 44.5 counts of difference (thus high to moderate agreement). At Grimso, ICC was poor to moderate and ranged between 0 and 0.59, whereas TDI remained low with estimates lower or equal to 1 count (thus high agreement). Despite a 100-fold lower abundance at Grimso, the same level of precision for nymphs could be achieved with a 70% increase of dragging effort. We conclude that the cloth-dragging technique is useful for surveying ticks and primarily to estimate abundance of the nymphal stage, whereas it rarely will be recommended for larvae and adults., Funding Agencies|Linkoping University; EU-Interreg OKS program ScandTick Innovation; EU-Interreg North Sea Region project NorthTick; Swedish University of Agricultural Sciences; Marie-Claire Cronstedts stiftelse; Lindesberg Municipality

ticks carry pathogens that can cause disease in both animals and humans, and there is a need to monitor the distribution and abundance of ticks and the pathogens they carry to pinpoint potential high risk areas for tick-borne disease transmission. In a joint Scandinavian study, we measured Ixodes ricinus instar abundance at 159 sites in southern Scandinavia in August-September, 2016, and collected 29,440 tick nymphs at 50 of these sites. We additionally measured abundance at 30 sites in August-September, 2017. We tested the 29,440 tick nymphs in pools of 10 in a Fluidigm real-time PCR chip to screen for 17 different tick-associated pathogens, 2 pathogen groups and 3 tick species. We present data on the geolocation, habitat type and instar abundance of the surveyed sites, as well as presence/absence of each pathogen in all analysed pools from the 50 collection sites and individual prevalence for each site. these data can be used alone or in combination with other data for predictive modelling and mapping of high-risk areas., Ticks carry pathogens that can cause disease in both animals and humans, and there is a need to monitor the distribution and abundance of ticks and the pathogens they carry to pinpoint potential high risk areas for tick-borne disease transmission. In a joint Scandinavian study, we measured Ixodes ricinus instar abundance at 159 sites in southern Scandinavia in August-September, 2016, and collected 29,440 tick nymphs at 50 of these sites. We additionally measured abundance at 30 sites in August-September, 2017. We tested the 29,440 tick nymphs in pools of 10 in a Fluidigm real-time PCR chip to screen for 17 different tick-associated pathogens, 2 pathogen groups and 3 tick species. We present data on the geolocation, habitat type and instar abundance of the surveyed sites, as well as presence/absence of each pathogen in all analysed pools from the 50 collection sites and individual prevalence for each site. These data can be used alone or in combination with other data for predictive modelling and mapping of high-risk areas.

Recently, focus on tick-borne diseases has increased as ticks and their pathogens have become widespread and represent a health problem in Europe. Understanding the epidemiology of tickborne infections requires the ability to predict and map tick abundance. We measured Ixodes ricinus abundance at 159 sites in southern Scandinavia from August-September, 2016. We used feld data and environmental variables to develop predictive abundance models using machine learning algorithms, and also tested these models on 2017 data. Larva and nymph abundance models had relatively high predictive power (normalized RMSE from 0.65–0.69, R2 from 0.52–0.58) whereas adult tick models performed poorly (normalized RMSE from 0.94–0.96, R2 from 0.04–0.10). Testing the models on 2017 data produced good results with normalized RMSE values from 0.59–1.13 and R2 from 0.18–0.69. The resulting 2016 maps corresponded well with known tick abundance and distribution in Scandinavia. The models were highly infuenced by temperature and vegetation, indicating that climate may be an important driver of I. ricinus distribution and abundance in Scandinavia. Despite varying results, the models predicted abundance in 2017 with high accuracy. The models are a frst step towards environmentally driven tick abundance models that can assist in determining risk areas and interpreting human incidence data.

Background: Tick-borne diseases have become increasingly common in recent decades and present a health problem in many parts of Europe. Control and prevention of these diseases require a better understanding of vector distribution. Aim: Our aim was to create a model able to predict the distribution of Ixodes ricinus nymphs in southern Scandinavia and to assess how this relates to risk of human exposure. Methods: We measured the presence of I. ricinus tick nymphs at 159 stratified random lowland forest and meadow sites in Denmark, Norway and Sweden by dragging 400 m transects from August to September 2016, representing a total distance of 63.6 km. Using climate and remote sensing environmental data and boosted regression tree modelling, we predicted the overall spatial distribution of I. ricinus nymphs in Scandinavia. To assess the potential public health impact, we combined the predicted tick distribution with human density maps to determine the proportion of people at risk. Results: Our model predicted the spatial distribution of I. ricinus nymphs with a sensitivity of 91% and a specificity of 60%. Temperature was one of the main drivers in the model followed by vegetation cover. Nymphs were restricted to only 17.5% of the modelled area but, respectively, 73.5%, 67.1% and 78.8% of the human populations lived within 5 km of these areas in Denmark, Norway and Sweden. Conclusion: The model suggests that increasing temperatures in the future may expand tick distribution geographically in northern Europe, but this may only affect a small additional proportion of the human population.

In recent years, focus on tick-borne diseases has increased as diseases such as Lyme disease and tick-borne encephalitis have become more common and represent a health problem in many parts of Scandinavia. More effective prevention of infections requires a better understanding of the factors affecting the vector abundance as well as human exposure to the vectors. Hence, there is a great need for analyses and models that can predict how vectors and their associated diseases are distributed now and possibly in the future. As a part of the ScandTick Innovation project, we surveyed tick nymphs at 159 sites (forests and meadows) in Denmark, southern Norway and south-eastern Sweden. At each site we measured presence/absence, and used the data obtained along with environmental data from satellite images to run Boosted Regression Tree machine learning algorithms to predict overall distribution in southern Scandinavia. Together with the predicted distribution maps, we used human density maps to identify and plot areas with high risk of exposure to ticks. The predicted distribution and the spatial variation found corresponded well with known distributions of ticks in Scandinavia (sensitivity: 91%, specificity: 60%), and we found that the model was predominantly temperature-driven. Because presence was strongly correlated with forested habitats the risk areas were much larger in Sweden and Norway compared to Denmark. When combining these distribution maps with human population density maps, we were able to quantify the proportion of people living in areas with tick presence in Scandinavia. We found that although tick nymphs were restricted to a small proportion of the modelled area, high proportions of the human populations (67-79%) lived within these same areas. The model suggests that a potential future range expansion of I. ricinus in Scandinavia is likely but may only affect a relatively small additional proportion of the human population.

Background: The epidemiology of the zoonotic tick-transmitted parasite Babesia spp. and its occurrence in wild reservoir hosts in Sweden is unclear. In European deer, several parasite species, including Babesia capreoli and the zoonotic B. venatorum and B. divergens has been reported previously. The European roe deer, Capreolus capreolus, is an important and common part of the indigenous fauna in Europe, as well as an important host for Ixodes ricinus ticks, the vector of several Babesia spp. in Europe. Here, we aimed to investigate the occurrence of Babesia spp. in roe deer in Sweden. Findings: Roe deer (n = 77) were caught and sampled for blood. Babesia spp. was detected with a PCR assay targeting the 18S rRNA gene. The prevalence of Babesia spp. was 52 %, and two species were detected; B. capreoli and B. venatorum in 44 and 7.8 % of the individuals, respectively. Infection occurred both in summer and winter. Conclusions: We showed that roe deer in Sweden, close to the edge of their northern inland distributional range, are infected with Babesia spp. The occurrence of B. venatorum in roe deer imply that it is established in Sweden and the zoonotic implication of this finding should be regarded to a greater extent in future., Funding Agencies|Lawski foundation (Sven och Lilly Lawskis fond for naturvetenskaplig forskning); Royal Physiographic Society in Lund; Royal Swedish Academy of Agriculture and Forestry [H14-0069-ALF]; Swedish Environmental Protection Agency project; Swedish hunters organization; foundation Marie-Clair Cronstedts stiftelse: RaFast; EU Interreg - ScandTick Innovation

In a fallow deer population in south western Sweden was female group size and group composition estimated. A possible rank order between female groups and the effects of this was also investigated. By using GPS-position from 11 marked females was home range size, preferred habitats and distance to preferred habitats determined and tested for relationship to rank order. Mean female home range size was 2.92km2 and preferred habitats were "Arable land", "Broad-leaved forest not on mire or open bedrock", and "Younger forest". Mean group size in mainly open areas was 72 individuals. Represented by the marked females there was a rank order found between female groups, and each marked female included in the rank study received a unique rank. There was a negative relationship between rank and home range size, the higher rank a female group did possess the smaller home range did it kept. Thus a high ranked group may not need to move over large areas to satisfy its requirements. This would mean less time to search for food and more time to forage and therefore an increased fitness. Further there was also a negative relationship between rank and area of preferred habitat, as high ranked female group kept a smaller area of the preferred habitats "Broad-leaved forest" and "Younger forest". This is related to a small home range that consists of smaller areas of preferred habitat in the same way a large home range consist of larger areas preferred habitat. This will however not mean that the low ranked group that keeps a large home range and large areas of preferred habitat always has access to all preferred habitats. Rather it is probably restricted at certain times by other groups with higher rank to one or several of these preferred areas and thus requires larger areas to alternate between. Finally, mean distance from home range centre to preferred habitat was smaller if the group had a higher rank. This is also related to the fact of a small home range in a high ranked group