Mathematical modeling of COVID-19 explored in recent webinar
Dr. Jonathan Dushoff, professor of Biology at McMaster University’s Institute for Infectious Disease Research, has spent nearly two decades doing dynamical modeling for infectious diseases. In a recent webinar he delivered with Sheena Guglani, research analyst at the eConsult Centre of Excellence (eConsult COE), Dushoff discussed the role of mathematical epidemiology in the context of COVID-19.
“You could say I’ve been getting ready for this pandemic for the last 15 to 20 years,” says Dushoff. “And I still wasn’t as well prepared as I should have been. But, on another level, nobody was really ready for this virus. There are so many difficult biological questions that have real relevance for managing the epidemic, and we’re scrambling to learn everything at once, and also to make good decisions based on partial knowledge.”
Missed the webinar? Watch it here
The webinar explored issues including flattening the curve and what’s next – topics that rely on dynamical models as tools to predict what will happen when we reopen.
Looking at transmission rates and social distancing in Korea, Dushoff talked about analyzing epidemic spread to predict health-care demand and to learn about what might happen as we ease social distancing measures. He also discussed trying to measure immunity, and possibly making use of people with immunity to protect others.
Guglani covered a qualitative perspective on infectious disease modeling, looking at key stakeholders – from journalists and public health professionals to government end users and academic modellers – to determine their perceptions and find out what key issues were of interest to these groups.
“The diverse stakeholder groups have many common concerns, such as the challenges in translating modelling results to public health,” says Guglani. “Nevertheless, mathematical modelling helps us to understand an outbreak and can put us on a better course of recovery than we might be otherwise.”
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