News – AI4Casting Hub

Measles Outbreak Tracking Tool in Action

The AI4Casting Hub team at the University of Guelph is excited to announce the launch of a community-focused public health interactive dashboard designed to track and forecast potential measles outbreaks (link). With measles cases nearly doubling in Ontario in the past two weeks and 14 confirmed cases in the Wellington-Dufferin-Guelph area since March 21, this tool is more crucial than ever.

How Can We Help?

Our Measles Outbreaks Dashboard is an interactive tool designed to track and predict the evolution of measles outbreaks, specifically targeting the 0-9 years old age group in the Wellington-Dufferin-Guelph PH region. This region encompasses around 33,500 children who regularly attend daycare and school. The dashboard features:

A compartmental model that tracks:
- Susceptible (S), Exposed (E), Isolated (L), Vaccinated (V), Recovered (R)
- Post-exposure vaccination (VL) for traced individuals

Adjustable Contact Rate settings to explore how changing interactions between children affects outbreak dynamics.

Real-time simulation of public health interventions such as contact tracing and isolation.

Incorporation of Vaccine Efficacy post-Exposure, considering timing and vaccine type.

On the 570 NewsRadio Kitchener, Professor Monica G. Cojocaru, Director of the AI4Casting Hub emphasized the tool’s importance during this surge in measles cases:

"Because measles is highly contagious, even a slight dip in vaccination coverage can increase the risk of outbreaks. Herd immunity requires around 95 percent vaccine coverage, but even a drop to 85 percent could trigger outbreaks."

The AI4Casting Hub isn’t just about numbers; it’s about helping health professionals and communities make informed decisions. By simulating different public health strategies, it demonstrates how vaccination rates, contact tracing speed, and isolation protocols directly affect outbreak prevention.

Professor Cojocaru points out the value of proactive measures:

"With this tool, we visualize and understand just how critical vaccination rates, contact tracing speed, and public health interventions are in preventing outbreaks."

Explore the Dashboard Now

Stay updated and take proactive steps in understanding how measles can spread and how interventions can make a difference. Visit our dashboard today!

For more comprehensive information on measles, check out Public Health Ontario and Public Health Canada official websites.

Professor with U of G using AI tool to track potential measles outbreaks

Using artificial intelligence to detect potential measles outbreaks

Measles cases in Ontario have nearly doubled over last 2 weeks

Canada’s top doctor concerned about measles outbreaks in Ontario, Quebec

Flu Activity Surges Across Canada

Recent data reveals a sharp increase in influenza activity across Canada, with the national positivity rate for influenza tests reaching 26.9%, the highest since the 2020-21 season. Older adults, particularly those aged 65 and over, are facing the highest rates of flu detections and hospitalizations. Provinces like Quebec, Prince Edward Island, and British Columbia are seeing especially elevated detection rates. The current flu season is marked by unusual co-circulation of both H3N2 and H1N1 strains, intensifying the severity of the outbreak. Experts warn that the convergence of these two strains is contributing to a dual outbreak scenario. Forecasting models from the AI4Casting Hub project a continued rise in influenza cases, potentially reaching a national positivity rate of 29.5% by mid-March 2025. As Canada navigates this flu season, experts highlight the need for adaptive forecasting and real-time data integration to enhance public health preparedness and response. For more updates on influenza trends, visit the AI4Casting Hub’s RVDSS Dashboard.

New Heuristic Algorithms to Solve Tough Problems in Sharing Resources

Researchers at the University of Guelph, under the direction of Dr. Monica Cojocaru, have achieved a significant advancement in artificial intelligence with the development of innovative heuristic algorithms. These algorithms are designed to tackle the intricate challenges associated with resource sharing, a problem that arises in numerous real-world scenarios, from environmental management to urban infrastructure planning.

Today We Reached Out to the Modelling Community!

We’re excited to share that the AI4Casting Hub has officially reached out to our broader modelling community, inviting researchers, students, and collaborators to join our initiative!

Over the past six months, with support from the University of Guelph, the Office of the Ontario Chief Medical Officer of Health, and Sanofi, and in collaboration with FluSight at the CDC and Hubverse at UMASS Amherst and UBC, we have worked hard to establish this publicly-facing, organized resource. Our mission is to elevate public discourse, inform policy, and provide training opportunities in disease forecasting.

Starting November 25, 2024, we invite researcher teams to submit weekly forecasts for Ontario and/or Canada to help provide insights into how flu, RSV, COVID, and other illnesses may evolve throughout the season. 🌟

AI4Casting Hub GitHub Repository: github.com/ai4castinghub

If you’re interested in learning more or would like to get involved, we encourage you to join our mailing list by November 20, 2024. Signing up will give you access to a 1-hour training workshop on November 22, where we’ll provide an overview of how the Hub operates and the supports we offer.

A big thank you to everyone who has supported us so far! Let’s work together to make this initiative a success.

We joined The hubverse!

We joined our colleagues in the Hubverse to continue to…

AI4Casting Hub Official Launch!

Dr. Monica Cojocaru and team, with support from University of…

Dr. Monica Cojocaru receives $300,000 to help improve preparedness for respiratory pathogen epidemics

The COVID-19 pandemic highlighted the profound impact of human behavior on the spread of infectious diseases. From mask-wearing and social distancing to vaccine hesitancy and pandemic fatigue, the dynamics of human behavior proved to be a critical challenge for governments and health agencies. The constantly evolving science and the public’s willingness to adopt health measures often left policymakers struggling to keep pace. To address these complexities, a groundbreaking collaboration between academia, industry, and government agencies aims to quantify how populations perceive and adopt public health policies. This partnership will investigate decision-making mechanisms at individual, group, and population levels, assessing how these behaviors influence the dynamics of pathogen transmission over time and across diverse geographic and socio-demographic categories.