Virus detection in questing ticks is not a sensitive indicator for risk assessment of tick-borne encephalitis in humans.

Tick-borne encephalitis virus (TBEV) is the most important tick-transmitted arbovirus causing human disease in Europe, but information on its endemic occurrence varies between countries because of differences in surveillance systems. Objective data are necessary to ascertain the disease risk for vaccination recommendations and other public health interventions. In two independent, separately planned projects, we used real-time RT-PCR to detect TBE virus in questing ticks. In Poland, 32 sampling sites were selected in 10 administrative districts located in regions where sporadic TBE cases were reported. In Germany, 18 sampling sites were selected in two districts located in a region with high TBE incidence. Altogether, >16,000 ticks were tested by real-time RT-PCR, with no sample testing positive for TBEV. A systematic search for published studies on TBEV prevalence in ticks in Poland and Germany also suggested that testing large numbers of collected ticks could not consistently assure virus detection in known endemic foci. Although assignment of results to administrative regions is essential for TBE risk mapping, this was possible in only 10 (investigating 22,417 ticks) of 15 published studies (>50,000 ticks) identified. We conclude that the collection and screening of ticks by real-time RT-PCR cannot be recommended for assessment of human TBE risk. Alternative methods of environmental TBEV monitoring should be considered, such as serological monitoring of rodents or other wildlife.

Determinants of tick-borne encephalitis virus antibody presence in roe deer (Capreolus capreolus) sera.

In order to identify variables associated with the presence of the tick-borne encephalitis (TBE) virus, we conducted a serological survey of roe deer [Capreolus capreolus (Artiodactyla: Cervidae, Linnaeus 1758)] in three forest districts of southern Hesse, Germany. Overall, 24 out of 105 (22.9%) of the sera were positive (≥1 : 10 plaque reduction neutralization test). Using a logistic regression approach, we found that unexplained spatial variation, indexed roe deer density (positive correlation), hind foot length of the tested roe deer (positive correlation) and infestation with female Ixodes spp. ticks (negative correlation) predicted the probability of TBE virus antibody presence in individual roe deer sera. Spring temperature increase and host sex were rejected as explanatory variables. We found considerable differences in TBE virus antibody seroprevalence (50.0% vs. 17.6%) between two forest districts located in the same county; this finding questions the current county-resolution of public health recordings. Given the high seroprevalence of roe deer and the considerable explanatory power of our model, our approach appears suitable to delineate science-based risk maps at a smaller spatial scale and to abandon the current human incidence per county criterion. Importantly, using roe deer as sentinels would eliminate the inherent bias of risk maps based on human incidence (varying levels of immunization and exposure of humans).

Attachment site selection of ticks on roe deer, Capreolus capreolus.

The spatio-temporal attachment site patterns of ticks feeding on their hosts can be of significance if co-feeding transmission (i.e. from tick to tick without a systemic infection of the host) of pathogens affects the persistence of a given disease. Using tick infestation data on roe deer, we analysed preferred attachment sites and niche width of Ixodes ticks (larvae, nymphs, males, females) and investigated the degree of inter- and intrastadial aggregation. The different development stages showed rather consistent attachment site patterns and relative narrow feeding site niches. Larvae were mostly found on the head and on the front legs of roe deer, nymphs reached highest densities on the head and highest adult densities were found on the neck of roe deer. The tick stages feeding (larvae, nymphs, females) on roe deer showed high degrees of intrastadial spatial aggregation, whereas males did not. Male ticks showed large feeding site overlap with female ticks. Feeding site overlap between larval-female and larval-nymphal ticks did occur especially during the months May-August on the head and front legs of roe deer and might allow pathogen transmission via co-feeding. Tick density, niche width and niche overlap on roe deer are mainly affected by seasonality, reflecting seasonal activity and abundance patterns of ticks. Since different tick development stages occur spatially and temporally clustered on roe deer, transmission experiments of tick-borne pathogens are urgently needed.

Body-mass or sex-biased tick parasitism in roe deer (Capreolus capreolus)? A GAMLSS approach.

Macroparasites feeding on wildlife hosts follow skewed distributions for which basic statistical approaches are of limited use. To predict Ixodes spp. tick burden on roe deer, we applied Generalized Additive Models for Location, Scale and Shape (GAMLSS) which allow incorporating a variable dispersion. We analysed tick burden of 78 roe deer, sampled in a forest region of Germany over a period of 20 months. Assuming a negative binomial error distribution and controlling for ambient temperature, we analysed whether host sex and body mass affected individual tick burdens. Models for larval and nymphal tick burden included host sex, with male hosts being more heavily infested than female ones. However, the influence of host sex on immature tick burden was associated with wide standard errors (nymphs) or the factor was marginally significant (larvae). Adult tick burden was positively correlated with host body mass. Thus, controlled for host body mass and ambient temperature, there is weak support for sex-biased parasitism in this system. Compared with models which assume linear relationships, GAMLSS provided a better fit. Adding a variable dispersion term improved only one of the four models. Yet, the potential of modelling dispersion as a function of variables appears promising for larger datasets.