PHAC - Substance Use Monitoring

The objective is to develop an innovative NLP-based surveillance system to monitor substance-related harms in real-time. This AI-driven solution will gather data from various media channels, synthesizing information to provide a comprehensive overview of substance use trends, clusters of morbidity, and mortality across Canada.

The project focuses on enhancing public health response, particularly for communities disproportionately affected by substance use. Traditional surveillance methods lag in data collection; this AI-powered system offers timely insights to empower early intervention and targeted public health action.

In collaboration with the Canadian Centre on Substance Use and Addiction, Datalab at the School of Health Policy and Management at York University, and the Urban Data Research Centre at the University of Toronto, this project is funded by the Public Health Agency of Canada’s Enhanced Surveillance for Chronic Disease Program.

Key Members

• Pam Kent, Canadian Centre on Substance Use and Addiction
• Vijay Mago, York University
• Mark Fox, University of Toronto
• Bart Gajderowicz, Utah State University
• Andrew Fisher, University of New Brunswick
• Kate Stoysich, Canadian Centre on Substance Use and Addiction
• Chealsea De Moor, Canadian Centre on Substance Use and Addiction