Community-level analysis of risk of vector-borne disease

Abstract

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.