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Lyme disease is an emerging public health threat in Canada. In this context, rapid detection of new risk areas is essential for timely application of prevention and control measures. In Canada, information on Lyme disease risk is collected through three surveillance activities: active tick surveillance, passive tick surveillance, and reported human cases. However, each method has shortcomings that limit its ability to rapidly and reliably identify new risk areas. We investigated the relationships between risk signals provided by human cases, passive and active tick surveillance to assess the performance of tick surveillance for early detection of emerging risk areas. We used regression models to investigate the relationships between the reported human cases, Ixodes scapularis (Say; Acari: Ixodidae) ticks collected on humans through passive surveillance and the density of nymphs collected by active surveillance from 2009 to 2014 in the province of Quebec. We then developed new risk indicators and validated their ability to discriminate risk levels used by provincial public health authorities. While there was a significant positive relationship between the risk signals provided all three surveillance methods, the strongest association was between passive tick surveillance and reported human cases. Passive tick submissions were a reasonable indicator of the abundance of ticks in the environment (sensitivity and specificity [Se and Sp] < 0.70), but were a much better indicator of municipalities with more than three human cases reported over 5 yr (Se = 0.88; Sp = 0.90). These results suggest that passive tick surveillance provides a timely and reliable signal of emerging risk areas for Lyme disease in Canada.