The Application of Remote Sensing and GIS Tools in the Study of Lyme Disease Risk Prediction

Lyme disease has become one of the most prevalent vector borne diseases in the United States and threatens to expand its territory if current warming trends continue. Many investigators propose that an increase in Lyme disease distribution may be caused by a shift in the habitat range of the blacklegged tick, Ixodes scapularis, as a response to climate change. Improved knowledge of the environmental factors related to the survival of I. scapularis is essential due to the unprecedented rate of increase in both regional distribution and abundance in North America over the past twenty years (Estrada-Peña 2002). Static maps of documented Lyme disease cases or tick presence may be helpful, but cannot be used to predict changes in disease risk over time. Nor do these maps provide additional information about the ecological processes responsible for changes in the vector’s expanding regional distribution. Scientists have devoted a considerable effort to studying the ecologic and social factors influencing tick abundance and distribution. However, the integration of these results into a model that explains tick colonization of new regions and changes in local abundance is still work in progress (Estrada-Peña 2002).