BACKGROUND: With the resurgence of tick-borne diseases such as Lyme disease and 
the emergence of new tick-borne pathogens such as Powassan virus, understanding 
what distinguishes vectors from non-vectors, and predicting undiscovered tick 
vectors is a crucial step towards mitigating disease risk in humans. We aimed to 
identify intrinsic traits that predict which Ixodes tick species are confirmed 
or strongly suspected to be vectors of zoonotic pathogens.
METHODS: We focused on the well-studied tick genus Ixodes from which many 
species are known to transmit zoonotic diseases to humans. We apply generalized 
boosted regression to interrogate over 90 features for over 240 species of 
Ixodes ticks to learn what intrinsic features distinguish zoonotic vectors from 
non-vector species. In addition to better understanding the biological 
underpinnings of tick vectorial capacity, the model generates a per species 
probability of being a zoonotic vector on the basis of intrinsic biological 
similarity with known Ixodes vector species.
RESULTS: Our model predicted vector status with over 91% accuracy, and 
identified 14 Ixodes species with high probabilities (80%) of transmitting 
infections from animal hosts to humans on the basis of their traits. 
Distinguishing characteristics of zoonotic tick vectors of Ixodes tick species 
include several anatomical structures that influence host seeking behavior and 
blood-feeding efficiency from a greater diversity of host species compared to 
non-vectors.
CONCLUSIONS: Overall, these results suggest that zoonotic tick vectors are most 
likely to be those species where adult females hold a fecundity advantage by 
producing more eggs per clutch, which develop into larvae that feed on a greater 
diversity of host species compared to non-vector species. These larvae develop 
into nymphs whose anatomy are well suited for more efficient and longer feeding 
times on soft-bodied hosts compared to non-vectors, leading to larger adult 
females with greater fecundity. In addition to identifying novel, testable 
hypotheses about intrinsic features driving vectorial capacity across Ixodes 
tick species, our model identifies particular Ixodes species with the highest 
probability of carrying zoonotic diseases, offering specific targets for 
increased zoonotic investigation and surveillance.