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Ecological community structure is particularly important in vector-borne zoonotic diseases with complex life cycles. Qualitative community model analysis may provide a meaningful alternative to standard population-based models of vector-borne
disease. We built on recent mathematical developments in qualitative community modeling coupled with conventional biomathematical models of vector-borne
disease transmission, to provide a procedure to analyze risk. Using this procedure, we can hypothesize changes in risk of vector-borne
disease from disturbances, such as control measures, habitat alteration, or global warming. We demonstrate the application of this procedure to an oak forest community to predict the risk of
Lyme disease. Our predictions of
Lyme disease risk in an oak forest community confirm reports of positive associations between deer abundance and risk of
disease and are consistent with published observations.