Extensive host sharing of central European Tula virus.

To examine the host association of Tula virus (TULV), a hantavirus present in large parts of Europe, we investigated a total of 791 rodents representing 469 Microtus arvalis and 322 Microtus agrestis animals from northeast, northwest, and southeast Germany, including geographical regions with sympatric occurrence of both vole species, for the presence of TULV infections. Based on serological investigation, reverse transcriptase PCR, and subsequent sequence analysis of partial small (S) and medium (M) segments, we herein show that TULV is carried not only by its commonly known host M. arvalis but also frequently by M. agrestis in different regions of Germany for a prolonged time period. At one trapping site, TULV was exclusively detected in M. agrestis, suggesting an isolated transmission cycle in this rodent reservoir separate from spillover infections of TULV-carrying M. arvalis. Phylogenetic analysis of the S and M segment sequences demonstrated geographical clustering of the TULV sequences irrespective of the host, M. arvalis or M. agrestis. The novel TULV lineages from northeast, northwest, and southeast Germany described here are clearly separated from each other and from other German, European, or Asian lineages, suggesting their stable geographical localization and fast sequence evolution. In conclusion, these results demonstrate that TULV represents a promiscuous hantavirus with a large panel of susceptible hosts. In addition, this may suggest an alternative evolution mode, other than a strict coevolution, for this virus in its Microtus hosts, which should be proven in further large-scale investigations on sympatric Microtus hosts.

Statistics and sample design in epidemiological studies of Echinococcus multilocularis in fox populations.

In this paper possible sampling strategies for estimating the prevalence of Echinococcus multilocularis infections in foxes are discussed. To draw valid conclusions from the analysis of fractions of a total fox population, each member of the total population must have the same chance of being selected for the investigation (random sampling), the sample must be representative with respect to all epidemiologically relevant conditions in the population (e.g. age, endemic status, seasonal effects, population density), and it must be large enough to obtain results with the required precision. For detection/exclusion of infections at a pre-specified prevalence threshold and confidence level (e.g. 99%), the required sample is rather small, but the information obtained from the data is limited. For prevalence estimates, the required sample sizes depend on the expected prevalence, the desired precision of the estimate and the chosen confidence level (e.g. 90, 95, or 99%). The samples need to be taken in spatial units where the variation of the conditions potentially influencing the infection can be neglected. A first impression of the spatial distribution of E. multilocularis infections in foxes can also be obtained by mapping the investigated sample (infected and uninfected animals) using the municipalities where they were shot or found as a spatial grid. To analyse the local influence of environmental factors, data on the geographical positions where the animals were sampled need to be collected and analysed in the context of a Geographic Information System (GIS).

Controlling Echinococcus multilocularis-ecological implications of field trials.

Two field trials to reduce the prevalence of Echinococcus multilocularis in foxes have been conducted in recent years. Although both trials reduced prevalence considerably, they failed to eradicate the parasite in the study region. Following the control trial in northern Germany, prevalence recovered unexpectedly and rapidly, reaching pre-control levels five quarters (15 months) after the end of control. To understand the internal dynamics of the parasite-host system's reaction to control, we developed a spatially explicit simulation model, Echi. The simulation model incorporates the information available concerning fox tapeworm population dynamics. Using epidemiological parameters to adjust pre-control prevalence, the model predicts the temporal evolution of the prevalence of E. multilocularis in controlled foxes without departing from the range of uncertainty of the field data. However, the model does not predict the rapid pre-control recovery observed in the field trial. The deviation of the model's prediction from field data indicates the involvement of processes not yet taken into account. We modified the model step by step to mimic processes with the potential to cause the rapid post-control recovery of the prevalence of E. multilocularis in foxes. Neither the longevity of tapeworm eggs nor the migratory behaviour of foxes showed any influence on the post-control reaction of the parasite-host system. However, landscape structures leading to a heterogeneous distribution of infected foxes have the potential to alter the system's reaction to control. If infected foxes are concentrated in multiple clusters in the landscape, the model prediction tallied with the range of uncertainty of the field data. Such spatial distribution of infected foxes may be caused by differential abiotic conditions influencing the survival of tapeworm eggs. The model was found to comply best with field data if the foxes acquire partial immunity by being exposed to the fox tapeworm. Both hypotheses explaining the rapid post-control recovery of the prevalence of E. multilocularis observed in the fox population were supported by field data. Both hypotheses have far-reaching consequences for future control trials. The spatial aggregation of infected foxes would enable control efforts to be concentrated on these highly infected areas. However, the acquisition of immunity acts as a buffer to control, necessitating intensified control measures.

Bayesian space-time analysis of Echinococcus multilocularis-infections in foxes.

A total of 26,220 foxes that were hunted or found dead in Thuringia, Germany, between 1990 and 2009 were examined for infection with Echinococcus multilocularis, the causative agent of human alveolar echinococcosis, and 6853 animals were found infected. The available data on the foxes including the location (local community; district) and the date of hunting/death were analyzed using a hierarchical Bayesian space-time model. The distribution of the model parameters and their variability was estimated on the basis of the sample size, the number of cases per spatial unit and time interval, and an adjacency matrix of the municipalities using a Markov Chain Monte Carlo simulation technique to assess the spatial and temporal changes in the distribution of the parasite. The model used to evaluate the data is widely applicable and can be applied to analyse data sets with gaps and variable sample sizes per spatial and temporal unit. In the study area, the prevalence of E. multilocularis increased from 11.9% (95% confidence interval 9.9-14.0%) in 1990 to 42.0% (39.1-44.1%) in 2005. While the infection was present in foxes only in the north-western parts of Thuringia in 1990, it had spread over the entire state by 2004. These results demand increased vigilance for human alveolar echinococcosis in Thuringia.

[Baiting intervals and duration of control of the small fox tapeworm: a simulation study]. / Köderauslageintervalle und Dauer der Bekämpfung des Kleinen Fuchsbandwurms: eine Modellierstudie.

Field trials to control the small fox tapeworm Echinococcus multilocularis failed to reduce the prevalence of the parasite persistently. With the experience from this empirical work, a simulation model for the population dynamics of the small fox tapeworm was developed. This model is used to examine the effect of different control strategies. Sufficient control duration is able to eradicate the parasite in simulation experiments. Baiting intervals of 4 or 6 weeks were found to be more efficient than shorter or longer intervals. The strategy used in field trials showed no sustainable effect in any of the simulation experiments. The applicability of simulation models for the planning of control measures for wildlife diseases is discussed.