Canadian Centre for Disease Modelling hosts 2022 Incubation Day

Visualization of the COVID-19 virus. Photo by Fusion Medical Animation on Unsplash

The Canadian Centre for Disease Modelling (CCDM) hosted the 2022 Incubation Day. The hybrid event took place May 16 to 17 and connected close to 200 postdocs, graduate students and undergraduate students around the world. 

 2022 Incubation Day local organizers and participants
2022 Incubation Day local organizers and participants

The 2022 CCDM Incubation Day was two-half days hybrid event, hosted in person at York University, facilitated by a HyFlex digital classroom, and broadcasted over Zoom, which was attended by participants from universities and institutions from Canada, the United States, China, and other countries. The event established a platform to inspire collaboration between disease modellers in the CCDM network. A Slack group was also established to continue serving as a forum for disease modelling research discussions.   

During the 2022 Incubation Day, CCDM brought together its graduate students and postdocs to showcase their research and promote communication within the CCDM network. The theme of the event was “Building a Network for Mathematical Modelling in Public Health: Centering Equity, Stakeholder Engagement and Policy,” and was organized by postdocs and graduate student volunteers, including planning, content creation and communication groups led by event advisors Memorial University Associate Professor Amy Hurford, University of Montreal Assistant Professor Bouchra Nasri, York University Assistant Professor Jude Dzevela Kong, University of New Brunswick Professor Lin Wang, York University Professor and York Research Chair Huaiping Zhu

York Professors Jianhong Wu, Jane Marie Heffernan, Seyed Moghadas, Neal Madras, Iain Moyles, Marina Freire-Gormaly, Hanna Jankowski, Hongmei Zhu, Xin Gao, Steven Wang, Woldegebriel Assefa Woldegerima, and Manos Papagelis, and more than 30 graduate students and postdocs also participated the event. 

The plenary talk by Nathaniel Osgood, professor in the Department of Computer Science at the University of Saskatchewan and director of the Computational Epidemiology and Public Health Informatics Laboratory, highlighted the importance of modelling in response to the pandemic through the talk “A call to service: Reflections on Health System Embedded Modelling.” Osgood mentioned, “infrastructure and organizational capability coupled with well-established track record anticipating service capacity needs for disease outbreaks, was crucial to hit the ground running,” and strengthened the importance of modelling, by stating that “if asked what is one of the most important component of our pandemic response, I would say it was the modelling (Andrew Will).”

The panel discussion was led by Michael Li and moderated by Iain Moyles. The panellists shared tips on careers available for infectious disease modellers and discussed career planning in diseases modelling
The panel discussion was led by Michael Li and moderated by Iain Moyles. The panellists shared tips on careers available for infectious disease modellers and discussed career planning in diseases modelling

A panel discussion was led by Michael Li, professor of mathematics at the University of Alberta; Victoria Ng, an epidemiologist and mathematical modeller at the Public Health Agency of Canada; James Ooi, site lead of the newly formed NRC‑Fields Institute Collaboration Centre; and Ashleight Tuite, an infectious disease epidemiologist, mathematical modeller, and assistant professor at University of Toronto’s Dalla Lana School of Public Health. The panel was moderated by Iain Moyles, assistant professor in the Department of Mathematics and Statistics at York University. 

The panellists shared great tips on careers available for infectious disease modellers – how to prepare for those careers, various breakthroughs in their lives, what worked for them, and what they look for when evaluating CVs. These tips were welcomed by students who benefited from the informative discussion to help navigate their own career paths.

Twenty-three postdocs and graduate students across the CCDM network presented their recent works, which was followed by insightful discussions. The student talks covered topics such as deterministic and stochastic models for infectious diseases, statistical and computational tools to study epidemiology, interpretation of disease parameters by social media, etc. Work presented by the postdocs and graduate students addressed various challenges in prediction and simulation of emerging and re-emerging diseases, ranging from evolution, control, transmission, spread, treatment and non-pharmaceutical interventions to behavioural patterns, as well as highlighted the impact of the network’s research on decision makers.  

The Director of Canadian Centre for Disease Modelling, Huaiping Zhu, said “The Incubation Day is a tradition which serves as a platform to showcase the achievement of our HQPs, postdocs and graduate students…this event has been going on for 10 years.” 

Wu, York University’s Distinguished Research Professor and founding director of CDM, introduced the background and history of the Incubation Day, mentioning, “It is the time from your exposure to the infections, this isn’t the real infection but it’s the passion and anticipating collaboration, that you are capable of fully passing on to the generations. And it is also a period that is susceptible to any inventions to create developments.” Wu also emphasized the importance of networking in his opening remarks.

Vivian Saridakis, associate dean of research and graduate education at York University, said “During the COVID-19 pandemic, mathematical modelling of diseases are an essential tool for government, researchers and policy advisers” and she encouraged our postdoc and graduate students to “meet people, establish collaborations, and come up some ideas,” through the Incubation Day.  

The CCDM, established in 2010, facilitates interdisciplinary research on disease modelling using cutting-edge mathematical and statistical techniques. To learn more, visit

The slack workspace for continued collaboration is available online. Those interested in joining, can connect through this link: