Climatic factors driving disease vector invasions in Europe: the tiger mosquito spread and other cases
Vortragender: Dr. Markus Neteler, GIS and Remote Sensing Unit at Fondazione Edmund Mach, Italy (Homepage)Do. 17.11.2011 (17:00-18:30)
Many continents, including Europe, are facing an increasing risk of introduction or spread of tropical vector-borne diseases transmitted by insects, ticks and rodents threatening human and animal health. Zoonoses already present in Europe include Tick-borne Encephalitis, Lyme disease, Leishmaniasis, Bluetongue, Chikungunya, and diseases caused by West Nile virus, Toscana virus and Hantavirus.
Since arthropod vectors such as ticks and insects are ectotherms, their activity depends directly on environmental conditions. Especially relevant is temperature which controls winter survival, vector population growth, feeding behavior, susceptibility of the vector to pathogens, synchrony among life stages, and the spread of the vectors to more northern latitudes.
Until 2100, an increase of winter minimum temperatures is expected in northern Europe along with increased annual precipitation, while in southern and central Europe higher-than-average summer temperatures are expected with a decrease of annual precipitation. Consequently, new ecological niches are being and are expected to be established and (re-)colonized by vectors along the northern limits of tick (e.g., Ixodes ricinus), tiger mosquito (Ae. albopictus), and sand fly (Diptera: Phlebotominae) distributions in Europe concurrent with the increase of the suitable habitat for these vectors.
Moreover, secondary infection routes have been recently identified: for example, the Chikungunya virus has been imported into a northern Italian region by a tourist returning from an endemic country, and it was transmitted to more than 200 people by Ae. albopictus. The presence of a competent vector would also allow local outbreaks in other regions when diseases are imported. The advent of high temporal resolution remote sensing data (e.g. gap-filled MODIS data) and the availability of long term historical and climatic data time series about future scenarios help to understand the epidemiology of diseases and to improve disease prevention and control.
Eingeladen GCE Prof. Beierkuhnlein
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