A University of Guelph professor hopes artificial intelligence will improve the detection of potential measles outbreaks.

As measles cases continue to rise in the city, an AI-powered project could help reverse that trend.

AI4Casting Hub is a forecasting project that creates interactive dashboards to detect potential outbreaks.

Monica Caojocaru, who leads the project, said by using the technology, she hopes it can warn the public and protect the community.

“We’re really hoping that having this tool will help the public,” Caojocaru said.

Wellington-Dufferin-Guelph Public Health reported seven cases in the area as of April 2.

She said the technology could also help public health officials become more proactive.

The tool, managed by the College of Engineering and Physical Sciences, gives users a direct hands-on trial learning experience, according to Caojocaru.

According to a release from the U of G, using AI to combine and analyze research-submitted data, the hub has been programmed to show how measles could spread among children up to nine years old based on real-world assumptions about contract tracing, days spent in isolation and more.

Contact tracing time is the number of days it takes public health to trace a child potentially exposed to a disease such as measles. Caojocaru said time is a critical variable; if contract tracing happens from one to three days, infections decrease. However, cases rise if it takes longer.

The hub also tracks vaccine hesitancy. Herd immunity is around 95 per cent, and Caojocaru said that even the smallest slip in vaccine coverage could trigger more outbreaks.

She said they’re working on incorporating wastewater surveillance data to help expand their AI forecasting on other diseases.

“The next step for the hub is to make use of this data and start looking at the emergence of particularly variants of the avian flu,” she said.