Data-driven predictions and novel hypotheses about zoonotic tick vectors from the genus Ixodes.

ABSTRACT:

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. I

SUBMITTER: Yang LH 

PROVIDER: S-EPMC5815220 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature