Study identifies ticks that are most dangerous to humans
What makes a tick more likely to transmit an infection from animals to humans? In the journal BMC Ecology, researchers answer that question using a machine learning method known as generalized boosted regression.  This type of algorithm helps identify features that are most important in predicting “a response variable (here, a binary variable designating whether the Ixodes tick species is a zoonotic vector) by building thousands of linked classification trees that successively improve upon the predictions of the previous tree,” the authors explain.
“Our model predicted vector status with over 91% accuracy,” the authors state, “and identified 14 Ixodes species with high probabilities (80%) of transmitting infections from animal hosts to humans on the basis of their traits.”
They found several intrinsic features that predict which tick is more likely to transmit an infection from animals to humans. These included:
- Ticks with the most eggs.
- Larger female ticks.
- Ticks which had fed on a greater number of hosts.
“With softer substrates like those encountered in human and other mammal hosts, ticks benefit from a more secure anchor conferred by deeper penetration of mouthparts that comprise the capitulum,” the authors state.
Therefore, the size of the capitulum may also affect the ability of a tick to transmit an infection. “Secure attachments lead to increased feeding times, which increase the probability of successful transmission for tick-borne pathogens,” the report states.
If these results are confirmed, scientists can re-evaluate species of ticks once considered harmless as possibly dangerous in transmitting disease.
As the authors point out, “these analyses also reveal several Ixodes species that are currently not recognized as vectors of zoonotic disease, but whose biological profile suggests they should be targets of future surveillance.”
- Yang LH, Han BA. Data-driven predictions and novel hypotheses about zoonotic tick vectors from the genus Ixodes. BMC Ecol. 2018;18(1):7.