A taxonomic revision of the Paranoplocephala primordialis (Douthitt) complex (Cestoda: Anoplocephalidae) in voles and squirrels

FIGURE 6. A. Scolex of Paranoplocephala nearctica n. sp. (ex. Microtus longicaudus, Alaska). B. Scolex of Paranoplocephala sp. (ex. Microtus oeconomus, Alaska). C. Mature proglottid of Paranoplocephala sp. (ex. Mi. oeconomus, Alaska). D. Mature proglottid of P. nearctica n. sp. (ex. Mi. longicaudus, Alaska). E. Gravid proglottids of Paranoplocephala sp. (ex. Mi. oeconomus, Alaska). Scale-bars in mm

Biome-specific rodent dynamics and hantavirus epidemiologies in Europe

Henttonen, H., Leirs, H., Kallio, E.R., Tersago, K., Voutilainen, L

Estimation of Local Values of Monthly Mean Temperature, Effective Temperature Sum and Precipitation Sum in Europe

The present paper presents a method for estimating the local values of meteorological variables from measurements in the vicinity of the subject point. Two interpolation methods are considered: the moving averages method, which calculates a weighted average of observations in the neighborhood of the subject point, and the combined method, which improves the moving averages estimate by utilizing the statistical dependence on latitude and altitude of the variables. The methods are applied to the estimation of the local values of monthly mean temperature, monthly precipitation sum, and the effective temperature sum in Europe. The input data consists of 30-year time series of monthly values from a network of meteorological stations, comprising 666 stations for monthly mean temperature and 517 for precipitation. The methods are tested by subtracting one station at a time from the observation network and calculating the values of the climatic variables from the rest of the data. The root mean square error (RMSE) of the smoothed mean temperature in the period May-August is approximately 0.7 degrees Centigrade, and that of the precipitation sum in the order of 70mm. In areas with a denser network of observations, the RMSE is lower

A phylogeny of members of the family Taeniidae based on the mitochondrial cox1 and nad1 gene data

nad1 gene dat

Maternal antibodies postpone hantavirus infection and enhance individual breeding success

The transfer of maternal antibodies from mother to progeny is a well-known phenomenon in avian and mammalian species. Optimally, they protect the newborn against the pathogens in the environment. The effect of maternal antibodies on microparasite transmission dynamics may have important consequences for both the fitness of the host and the epizootic processes of the pathogens. However, there is a scarcity of studies examining these effects in free-living wild species. We studied the influence of maternal antibodies against the zoonotic Puumala hantavirus (PUUV) on the fitness of bank voles (Clethrionomys glareolus) and on PUUV transmission by exposing young maternal antibody-positive (MatAb+) and negative (MatAb−) bank voles (n=160) to PUUV in experimental populations. PUUV-specific maternal antibodies delayed the timing of infection. Females were more susceptible to PUUV infection than males. Interestingly, both the females and the males with maternal antibodies matured earlier than the other individuals in the population. Our results highlight the significance of maternal antibodies in the transmission of a pathogen and in the breeding success of the carriers

Towards integrated surveillance of zoonoses : spatiotemporal joint modeling of rodent population data and human tularemia cases in Finland

Abstract Background There are an increasing number of geo-coded information streams available which could improve public health surveillance accuracy and efficiency when properly integrated. Specifically, for zoonotic diseases, knowledge of spatial and temporal patterns of animal host distribution can be used to raise awareness of human risk and enhance early prediction accuracy of human incidence. Methods To this end, we develop a spatiotemporal joint modeling framework to integrate human case data and animal host data to offer a modeling alternative for combining multiple surveillance data streams in a novel way. A case study is provided of spatiotemporal modeling of human tularemia incidence and rodent population data from Finnish health care districts during years 1995–2012. Results Spatial and temporal information of rodent abundance was shown to be useful in predicting human cases and in improving tularemia risk estimates in 40 and 75% of health care districts, respectively. The human relative risk estimates’ standard deviation with rodent’s information incorporated are smaller than those from the model that has only human incidence. Conclusions These results support the integration of rodent population variables to reduce the uncertainty of tularemia risk estimates. However, more information on several covariates such as environmental, behavioral, and socio-economic factors can be investigated further to deeper understand the zoonotic relationship