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When then-Alberta Premier Jason Kenney addressed the province in March 2020 with dire predictions about the impact of the COVID-19 pandemic, many were shocked at the numbers.

In what  as many as 800,000 Albertans would be infected by the virus, while between 400 and 3,100 could die before the end of that summer. Ultimately, the predictions were inaccurate. No one could have foreseen how the next three years would unfold.

A Schulich School of Engineering professor is hoping to help experts make more-informed decisions with any future virus as he undertakes a new five-year study looking at demographics, geography and more.

Dr. Richard Wan, PhD, says data collected during the pandemic will help his multidisciplinary team create the computational framework for the international study, which received a grant from the Natural Sciences and Engineering Research Council of Canada.

Analyzing a wide swath of information

Wan says trying to determine how a virus will travel through a population isn’t as simple as looking at where someone lives or how often they visit with others.

He says combining mechanics principles with existing social, epidemiological and economics models to find an approach to modelling virus transmission under new variants and differing levels of immunity is a new concept.

“The disease spread in a suburb of Calgary can be very different from that observed for another suburb of Calgary,” says Wan, a professor in the .

“Readily available data on the demographics, and socio-cultural aspects — including subtle facts such as compliance with guidelines, multigenerational households, delays in seeing a doctor, and cultural customs — will be central to our studies and integrated into the model.”

It will be a lot of numbers, Wan says, but the machine-learning-assisted model will be able to address various population sizes, from households and schools to communities, cities, countries and even the whole planet, if needed.

Studying the global village

During the height of the pandemic, some tried to compare it to the Spanish flu pandemic of 1918-1920, which was the most severe influenza outbreak of the 20^th century and among the most devastating pandemics in human history, with an estimated 500 million cases and a death toll of up to 50 million.

One of the biggest differences between the two was how, a century later, the world has become a global village with people having the ability to travel great distances in short amounts of time.

However, Wan says, technology has also made it easier to track people in real time.

“Mobility data collected by telecom companies like Google and Facebook can be made accessible as long as they are released by the government,” he says. “These datasets are crucial for understanding the spatiotemporal dynamics of human mobility together with virus circulation.”

Researching for the future

During the study, Wan and his team will be looking to compare the evolution of the pandemic between Canada and France.

Despite having similar gross domestic product, he says Canada is a very large, diverse country while France is a small, less-diverse country.

“We can expect the dynamics of virus spread to be substantially different despite fighting the same pathogen,” Wan says.

“Individual behavioural reactions such as compliance with preventive measures as well as government actions for vaccination are also different due to cultural differences in values.”

The research group includes Dr. Kerry Black, PhD, Schulich School of Engineering; Dr. Tyler Williamson, BSc’05, PhD’11, and Dr. Craig Jenne, PhD’05, Cumming School of Medicine; as well as two geomechanics experts from France: Dr. Francois Nicot, PhD, and Dr. Antoine Wautier, PhD. Wan says several other PhD, postdoctoral and summer research students will also be involved.

Wan says the multidisciplinary approach to this project will be key to delivering accurate and incisive models when the next COVID-19 comes around.

“Success of this project would mean generating solutions that will inform policy-makers and health-service providers about pandemic management for forthcoming new waves or pathogens,” Wan says. “Knowing the viral load likely to cause infection in people of different ages, with varying underlying health risks and socio-cultural challenges, including Indigenous people, is critical.”

He also expects the research results will be published in well-respected journals in related fields for future generations to learn from.