Zoonotic Transmission of Pathogens by Ixodes ricinus Ticks, Romania

For the first time, DNA from human pathogenic R. helvetica (7.5%), R. monacensis (6.1%), A. phagocytophilum (1.4%), E. muris (0.7%), F. tularensis (2.7%) and Babesia sp.EU1 (0.7%) has been detected in Romania. The tick Ixodes ricinus is one of the most important vectors of a large variety of pathogens of veterinary and medical importance in Europe (1). The most prevalent I. ricinus-borne infection in humans in Europe is Lyme borreliosis, a multisystemic disorder caused by spirochetes of the Borrelia burgdorferi sensu lato complex (2) .

Tick-borne viruses in Europe

The aim of this review is to present briefly background information on 27 tick-borne viruses ("tiboviruses") that have been detected in Europe, viz flaviviruses tick-borne encephalitis (TBEV), louping-ill (LIV), Tyuleniy (TYUV), and Meaban (MEAV); orthobunyaviruses Bahig (BAHV) and Matruh (MTRV); phleboviruses Grand Arbaud (GAV), Ponteves (PTVV), Uukuniemi (UUKV), Zaliv Terpeniya (ZTV), and St.

Effects of deer density on tick infestation of rodents and the hazard of tick-borne encephalitis. I: empirical assessment.

Tick borne encephalitis (TBE) is endemic to eastern and central Europe with broad temporal and spatial variation in infection risk. Although many studies have focused on understanding the environmental and socio-economic factors affecting exposure of humans to TBE, comparatively little research has been devoted to assessing the underlying ecological mechanisms of TBE occurrence in enzootic cycles, and therefore TBE hazard.

Consequences of landscape fragmentation on Lyme disease risk: a cellular automata approach

The abundance of infected Ixodid ticks is an important component of human risk of Lyme disease, and various empirical studies have shown that this is associated, at least in part, to landscape fragmentation. In this study, we aimed at exploring how varying woodland fragmentation patterns affect the risk of Lyme disease, through infected tick abundance. A cellular automata model was developed, incorporating a heterogeneous landscape with three interactive components: an age-structured tick population, a classical disease transmission function, and hosts.

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