A Risk Model for the Lyme Disease Vector Ixodes scapularis (Acari: Ixodidae) in the Prairie Provinces of Canada

Lyme disease is emerging in Canada due to geographic range expansion of the tick vector Ixodes scapularis Say. Recent areas of emergence include parts of the southeastern Canadian Prairie region. We developed a map of potential risk areas for future I. scapularis establishment in the Canadian Prairie Provinces. Six I. scapularis risk algorithms were developed using different formulations of three indices for environmental suitability: temperature using annual cumulative degree-days > 0 °C (DD > 0 °C; obtained from Moderate Resolution Imaging Spectroradiometer satellite data as an index of conditions that allow I. scapularis to complete its life cycle), habitat as a combined geolayer of forest cover and agricultural land use, and rainfall. The relative performance of these risk algorithms was assessed using receiver-operating characteristic (ROC) area under the curve (AUC) analysis with data on presence–absence of I. scapularis obtained from recent field surveillance in the Prairie Provinces accumulated from a number of sources. The ROC AUC values for the risk algorithms were significantly different (P < 0.01). The algorithm with six categories of DD > 0 °C, habitat as a simple dichotomous variable of presence or absence of forest, and normalized rainfall had the highest AUC of 0.74, representing “fair to good” performance of the risk algorithm. This algorithm had good (>80%) sensitivity in predicting positive I. scapularis surveillance sites, but low (50%) specificity as expected in this region where not all environmentally suitable habitats are expected to be occupied. Further prospective studies are needed to validate and perhaps improve the risk algorithm.