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Tick Identification to Combat Lyme Disease

Photo credit: Jim Gathany

By Ian Gormely

Toronto – Today, the Vector Institute, an independent, not-for-profit research institute focused on leading-edge machine learning, announced the third of its series of Pathfinder Projects to implement artificial intelligence (AI) in the health sector.

The third Pathfinder Project, performed in partnership with Public Health Ontario (PHO), will classify tick species using computer vision. Blacklegged ticks are the only ticks in Ontario known to carry B. burgdorferi, the bacteria that causes Lyme disease. Not all blacklegged ticks carry B. burgdorferi, but a bite from one is of more concern than a bite from a dog tick or another tick species that doesn’t carry the bacteria. For this project, Vector’s technical AI staff scientist Dr. Elham Dolatabadi, Dr. Vanessa Allen, Chief of Microbiology, PHO and Dr. Samir Patel, clinical microbiologist at PHO, will develop a method to automatically identify tick species using computer vision.

The first deliverable will be an AI algorithm that professionals at PHO will use to identify whether or not a tick is a blacklegged tick. The long-term goal is to create an app that anyone can use to simply take a photo of a tick. Once the app identifies the species, it will provide advice.

“The app we want to build would empower the public,” says Dr. Patel. PHO receives around 10,000 ticks each year for identification. Currently, the PHO laboratory has to identify each individual tick that is submitted. “Manually identifying and reporting each tick back to the submitter can take up to three weeks,” he says. The process can be automated using machine learning approaches so it is faster at PHO in the short term. “Once the app is developed the process will be even faster because the app can tell you right away whether or not it is a blacklegged tick and infer the risk of contracting Lyme disease.” The rapid identification of the blacklegged ticks will allow individuals to determine whether or not they should seek medical attention within the recommended 72 hours of tick removal.

Pathfinder Projects are small-scale efforts designed to produce results in 12 to 18 months that guide future research and technology adoption. With technical and resource support from the Vector Institute, the projects each bring together a multidisciplinary research team to tackle an important health care problem or opportunity using machine learning and AI more broadly. Each project was chosen for its potential to help identify a “path” through which world-class machine learning research can be translated into widespread benefits for patients.

About the Vector Institute

The Vector Institute is an independent, not-for-profit corporation dedicated to advancing artificial intelligence, excelling in machine and deep learning. The Vector Institute’s vision is to drive excellence and leadership in Canada’s knowledge, creation, and use of AI to foster economic growth and improve the lives of Canadians.

The Vector Institute is funded by the Province of Ontario, the Government of Canada through the Pan-Canadian AI Strategy administered by CIFAR, and industry sponsors from across the Canadian economy.

Tick Identification

Ticks, and the threat of Lyme disease, have become a regular feature of venturing outdoors in the summer months. For many Canadians, a thorough check for the tiny insects, which feed on our blood, is par for the course when returning from a hike or camping trip. Yet, only certain tick species actually carry the bacteria that causes Lyme disease. The challenge for most Ontarians is correctly identifying the type of tick that has decided to make you its lunch.

“Half of the ticks in Ontario are dog ticks,” explains Dr. Samir Patel, clinical microbiologist with Public Health Ontario (PHO). “They don’t carry the bacteria that causes Lyme disease.” However, blacklegged ticks are capable of carrying and transmitting that bacteria, with the risk of infection higher in certain parts of the province than others. Anyone who finds one on their body should consult a doctor.

PHO receives over 10,000 tick submissions every year — ticks sent to their laboratory site in Sault Ste. Marie — from Ontarians looking for guidance around a potential tick bite. Currently the laboratory has to manually identify each bug, a process that can take up to three weeks.

To ensure rapid and streamlined medical assessment of high risk tick bites, as well as reduce individuals’ anxiety about the potential Lyme disease after a tick bite, PHO is developing a mobile app to rapidly and accurately identify tick species and provide next-steps medical guidance. “There’s currently a gap in care,” admits Dr. Vanessa Allen, Chief of Medical Microbiology at PHO, “and this is one way to close that gap and improve the care and the delivery of services for Lyme disease in Ontario and beyond.”

Along with Dr. Allen and Vector’s technical AI staff scientist, Dr. Elham Dolatabadi, Dr. Patel is currently developing a computer vision model to differentiate between the two common tick species normally found in Ontario. “In the short-term we look forward to using computer vision for blacklegged tick identification at PHO.” he says. “Once the app is developed, it will empower the public. If you find a tick on your body, the app will be able to tell you right away whether it is a blacklegged tick or not.”

Tick populations have been increasing in recent years, as has awareness around tick bites and the threat of Lyme disease, says Dr. Allen. But both she and Dr. Patel caution that a tick bite, even from a blacklegged tick, doesn’t automatically mean that a person will contract Lyme disease and where appropriate, a single dose of prophylaxis should mitigate the chances of infection.

PHO plans to have the app available to the public by the end of next year. They also hope to use data from the user-submitted photos to help track tick populations in the province and better understand where ticks are moving, which can help inform future strategies, says Dr. Allen. “It’s not a magic bullet, but it’s a tool to speed up the process of both patient care and our understanding of Lyme disease.”