The drug-poisoning crisis in Ontario has worsened dramatically since the introduction of fentanyl in 2016 and was only exacerbated by the COVID-19 pandemic. Surveillance methods are still limited in their ability to detect this ever-evolving crisis, especially novel contamination events. The Automated Opioid News Event-based Surveillance system (AONES) is a tool that operates in near real-time, using artificial intelligence (AI) to identify news articles related to opioids and extract data related to the unregulated drug supply. It was developed through a Public Health Ontario Locally Driven Collaborative Project grant. The tool is publicly available from AONES (kflaphi.ca) to aid public health staff and others working in substance use harm reduction. This PHO Rounds will introduce and explain the tool, including providing a demo and a discussion of the opportunities and limitations in using event-based surveillance systems and AI for opioid surveillance.
A second PHO Rounds will present on our use of natural language processing and AI based technologies to develop public health tools such as AONES.
By the end of this session, participants will be able to:
• Identify potential uses of artificial intelligence in supporting event-based surveillance systems
• Describe how the AONES tool can be used to support public health surveillance and harm reduction activities
• Use the AONES tool to retrieve information on the unregulated drug supply
• Interpret the AONES data in light of the limitations of event-based surveillance systems and the application of AI
Presenter(s): Allison Maier and Nancy Slipp
The presentation can be found here: [ Ссылка ]
