What Makes Ticks Tick? Using Your Tick Encounters to Predict Lyme Disease Risk

A black-legged tick. Courtesy of: Robert Webster

By Jean-Paul R. Soucy

This lovely critter, no larger than a sesame seed, is a black-legged tick (Ixodes scapularis). This species’ bite is responsible for transmitting Lyme disease in most areas of Canada and the United States. Lyme disease affects thousands of Canadians each year and causes symptoms like fever, fatigue, and chills, which can turn into arthritis, neurological issues, and even heart problems if untreated.

Given the severity of this disease, it makes sense that we might want to know where in our environment this perilous parasite is likely to show up. This information can help public health authorities decide where to target pest control efforts or choose where to display warning signage. The black-legged tick dries out easily and generally prefers cool, damp environments such as under the leaf litter present in deciduous forests. However, the speed of the tick’s development is directly tied to climate, so areas that aren’t warm enough will mean that ticks in that area will be unlikely to develop and reproduce. Additionally, as a parasite, the black-legged tick needs access to specific animal hosts in order to complete its life cycle. There’s a lot to think about when it comes to figuring out where black-legged ticks might be!

The simplest way to discover if ticks are in a particular area is to go out and look for them. However, this is expensive and time-consuming and as a result can only be done over small areas. What if there was a way to predict the occurrence of black-legged ticks over a large area using data that already exist? Well, there is, using ticks submitted by members of the public for identification and disease testing (not all black-legged ticks carry Lyme disease). If these submissions mention where the tick was collected, we can correlate these points with the values of environmental variables (such as mean annual temperature or distance to water) at these points to detect if any of these variables are associated with the presence of ticks. These relationships can then used to make predictions about the presence of ticks anywhere in a region of interest. This process is called species distribution modelling. In my 2018 paper on Lyme disease risk in Ottawa, Ontario, we did just that using ticks submitted to Ottawa Public Health and free land cover data from the Ontario’s Ministry of Natural Resources and Forestry.

In this study, we considered a number of variables that might be connected to black-legged ticks, including the distance from treed areas, elevation, and the nearby availability of water. Our plan was to compare the values of these variables at the locations that members of the public had found ticks to the values of these variables at points randomly selected from the entire region of Ottawa. If tick presence was correlated with being close to trees, for example, we would expect our tick points to be closer on average to trees than points randomly selected from the whole region.

There’s just one problem with this approach—we haven’t accounted for bias in how our tick presence points were collected. Remember that people generally travel to places they can access easily; in other words, people tend to stick close to roads. If we try to make predictions without accounting for this bias, we would in fact be predicting where roads are, not ticks! Thus, to make the comparison fair, we have to compare the values of environmental variables at tick presence points to randomly selected points near roads in Ottawa.

Heat map predicted tick occurence Ottawa

Predicted tick occurrence in Ottawa, Ontario. Courtesy of: Soucy et al. 2018.

Above is our final map for predicted tick presence in Ottawa. Red areas are more likely to contain ticks, whereas blue areas are less likely. We tested our predictions by looking for ticks at 17 sites in Ottawa. The results of this study were largely consistent with our predictions, as we tended to find ticks (positive sites) in red areas but not find them (negative sites) in blue areas. Among the variables we studied, we found that distance from treed areas, distance from agriculture, and water availability best predicted tick presence.

How do we know that these variables actually cause tick presence, rather than just being correlated with them? Well, we don’t. This is where expert knowledge of tick biology comes in to identify plausible relationships. As previously mentioned, ticks thrive in the cool, damp environments provided by deciduous leaf litter. And deer, the hosts for the adult black-legged tick, require access to a reliable source of water.

I hope this post helps to shed some light on how researchers use data provided by citizens and governments (paid for by citizens!) in order to produce maps to assist with combating infectious disease threats.

If you’ve been bitten by a tick and would like to learn how to submit it for Lyme disease testing in Canada, please click here or contact your local public health authority. This project and others like it would not have been possible without the assistance of people like you.

Click here to learn how to avoid being bitten by black-legged ticks (Centers for Disease Control and Prevention).

You can read the full open access publication that inspired this post in Vector-Borne and Zoonotic Diseases.

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