Hosted by: The Public Health Agency of Canada (PHAC)’s Data, Surveillance and Foresight Branch (DSFB) and National Collaborating Centre for Infectious Diseases (NCCID).
Date and time: May 27, 2025 | 1:00 to 2:00 Eastern Time / 12:00 to 1:00 Central Time
Language: English
Introduction
Please join us on Tuesday, May 27, 2025 1:00 to 2:00 ET (10:00 to 11:00 PT), for the eighth seminar of the 2024-2025 Surveillance Advances season, “Establishing a Surveillance, Early Warning, and Forecasting System for Avian Influenza Outbreaks in Canada.”
Beginning in November 2021, Canada has repeatedly contended with outbreaks of the H5N1 strain of avian influenza, impacting both domestic poultry and wild bird populations. These outbreaks have not only posed public health risks but also caused widespread disruption and significant economic damage within the bird farming industry.
While existing surveillance techniques, such as environmental sampling from water, soil, air, and bird enclosures, are standard, they are often labor-intensive and expensive, limiting timely response. To overcome these challenges, this study introduces a new digital-based surveillance approach and Early Warning System (EWS) that harnesses publicly available web data to track and anticipate avian influenza outbreaks with greater speed and efficiency.
The system analyzes multiple online data sources, including weather and air quality reports, media coverage, social media trends, and Google search patterns, that show strong associations with outbreak events. By applying deep learning methods such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models, this framework predicts potential outbreaks across Canada, both nationally and regionally. This data-driven strategy is intended to aid regulatory agencies, poultry producers, and public health officials in taking pre-emptive measures, ultimately aiming to minimize the spread of the virus and reduce the risk of it crossing over to humans or other animals.
Learning Objectives
- Understand the limitations of traditional avian influenza surveillance methods and the need for more efficient monitoring systems.
- Explain how integrating diverse web-based data sources (such as weather, media, social media, and search trends) can improve the detection and prediction of avian influenza outbreaks.
- Describe the role of deep learning models like LSTM and GRU in forecasting avian influenza outbreaks and supporting proactive public health interventions.
Speaker
- Dr. Zahra Movahedi Nia, Research Associate, PhD in Computer Engineering, York University
Dr. Zahra Movahedi Nia is a research associate at York University and a data scientist at AI4PEP Global south, specializing in machine learning, data analytics, and Natural Language Processing (NLP). Holding a Ph.D. in computer engineering, Zahra has spent three years as a postdoctoral researcher at York University, where they have developed a novel early warning system for respiratory infections through web-based data sources. Zahra’s primary research program is centered on the integration of Artificial Intelligence (AI) and data science to enhance decision-making processes in clinical public health. Through the development of advanced machine learning models and data mining methods, she aims to address complex health challenges by providing data-driven insights and predictive tools that inform healthcare policies and interventions. Outside of academia, Zahra is invested in the development of Large Language Models (LLMs) with the potential to offer anonymous medical consultation support to individuals, broadening access to reliable health information while maintaining privacy. She is deeply devoted to bridging the gap between cutting-edge AI technologies and practical healthcare solutions, aiming to create tools that empower both individuals and healthcare providers.
Moderators
- Robert Sager, NCCID
Format
This seminar will be held on Zoom. The presentation will be 30 minutes followed by approximately 15 minutes for a discussion and question period from attendees. Presentation materials in English and French will be distributed through NCCID media channels.
Access Instructions
All instructions for the seminar series will be posted on the Zoom registration page and will be emailed to all registrants prior to the event.
Past Webinars
Surveillance Advances launched in September 2023 with a discussion about the foundational concepts of public health surveillance and the future opportunities that lie ahead. Subsequent seminars featured topics related to health inequalities (seminar 2), data science (seminar 3), maternal and newborn health (seminar 4), and injury surveillance (seminar 5). For a complete list of seminars and to view their recordings, please visit the Surveillance Advances webcasts page
Accreditation Statement
Surveillance Advances is a self-approved group learning activity (Section 1) as defined by the Maintenance of Certification Program of the Royal College of Physicians and Surgeons of Canada. Surveillance Advances is also approved by the Council of Professional Experience for professional development hours for members of the Canadian Institute of Public Health Inspectors.
