EPISTISSpatio-temporal risk assessment of Foot and Mouth Disease at the wildlife-livestock interface of the Kruger National Park The EPISTIS (EPIdemiological Space-Time Information System) Project aims at using a combination of ground data collected in everyday disease management programs as well as remotely sensed data, to better understand the dynamics of disease risk at the wildlife-livestock interface.  Foot and Mouth Disease (FMD) was chosen for its potential devastating impact on both local and regional agricultural economies as well as the fact that FMD is naturally present in wildlife populations (notably African buffaloes) in the Kruger National Park (KNP). Having a natural wildlife host, makes eradication of the disease in the foreseeable future unlikely, further emphasizing the need for interventions that are effective in both space and time and adapting to changes in both the environment as well as control strategies. The basis for the project lies in the distribution and density modelling of the two main hosts of the disease, cattle and buffaloes. Strangely enough, very little is known about the grazing patterns of communally farmed cattle along the boundaries of KNP, even though communal livestock farming comprises the major land use class adjoining KNP. Therefore, the EPISTIS project set out to track a number of communal as well as commercial cattle along the western boundary of KNP for one year with HOTGROUP GPS/GSM collars. These data are now being analysed to find linkages between grazing patterns and seasonal environmental changes, landscape features, land use practices, etc as can be measured through satellite imagery. Once such relationships have been found and described, they can be used to predict the distribution and density of cattle in the whole area adjoining KNP. Using a similar approach, buffalo distribution and density can also be predicted inside, and occasionally outside, the Park.
Finally, by adding additional information on real-time disease control measures (such as fences and vaccination) to these dynamic distribution/density models, one can get a realistic picture of where the highest risk of contact between buffaloes and susceptible cattle exist at a certain point in space/time under a specific set of environmental conditions. This kind of information is potentially useful to plan and prioritize control strategies and interventions. Such a tool could also be applied to other similar diseases with both wildlife and livestock hosts. The project is currently in its final year of implementation and hope to produce useful results towards the end of 2010.
The EPISTIS projected is funded through the STEREO II grant of BELSPO and has been supported in kind and through advice by HOTGROUP.
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