Context and objectives
Tick-borne diseases are currently the most important diseases carried by arthropod vectors in Europe, infecting thousands of people annually, including many recreational users of forests. Because ticks, and the animals they feed on, have specific environmental needs, they can be closely associated to certain specific environmental factors, many of which can be monitored using remotely sensed data. Such data can be included in models relating either the presence or abundance of the vector or disease presence or incidence with a diversity of variables derived from satellite data. Such models can help us understand which environments are the most favourable to ticks and the pathogens they transmit, that is, the most potentially dangerous to people from an arthropod-borne disease standpoint. However, many models so far have focused on environmental factors operating at one spatial scale: either the fine spatial scale of the landscape, examining for example the importance of forest, or at broad scale, focusing then on regional variations in the climate.
Expected scientific results
Results indicated that as we hypothesised, factors operating at various scales contribute to explaining the spatial distribution of tick borne diseases. Also, the spatial distribution is the result of the combination not only of environmental factors, but also of factors pertaining to the way human societies manage landscapes and come into contact with them. The combination of various scales of study is not often realised in environmental studies, and also not in disease ecology. The project also facilitated the collating and updating of data on ticks and on Lyme borreliosis in Belgium. One clear need highlighted by the study is for disease surveillance systems to be put in place that might allow a thorough investigation of spatial variation in the distribution. This will be key to bring further the understanding of environmental factors of the spatial distribution of arthropod-borne diseases. The value of remotely sensed data in the study of disease ecology was once more highlighted, but the challenge of identifying adequate proxies for biological and human phenomena persist.
|Project leader(s):||UCL - Georges Lemaître Centre for Earth and Climate Research|