Omicron making life difficult for mathematicians trying to track COVID-19
Global News
The highly transmissible Omicron variant is forcing mathematicians to rework the models that have helped shaped Canada's understanding of COVID-19.
The highly transmissible Omicron variant is forcing mathematicians to rework the models that have helped shaped Canada’s understanding of COVID-19, as well as the country’s response to the pandemic.
Everything from who gets tested to who’s most likely to contract the virus has changed with the latest wave of the pandemic, and that’s posing distinct challenges for those who model its impact, says Caroline Colijn, an associate professor of mathematics at Simon Fraser University in British Columbia.
In particular, Colijn said it will be difficult to understand the severity of the disease as it spreads through a mostly vaccinated public.
“We’re still adapting to flying blind in terms of reported cases,” she said in an interview. “Hospitalizations are lagging and there’s not always good data on them, and (hospitalization numbers) won’t tell you as directly about infections as reported cases will.”
Better hospitalization data could help – like daily admission numbers for COVID-19 patients as well as stats on those who were hospitalized for other reasons but tested positive for COVID-19 while in care – but it’s complicated, she said.
For example, if hospitalizations are low, like they are in Newfoundland and Labrador, that kind of information could be a privacy breach. “It’s a challenge,” Colijn said.
As the Omicron variant drove weeks of record-breaking case counts across the country, provincial governments stopped testing for every possible case of COVID-19 – the testing and tracing demand was overwhelming and it was impossible to keep up. Instead, provinces such as British Columbia, Ontario and Newfoundland and Labrador are now only testing for cases among those who have a higher risk for infection and hospitalization, like people in long-term care homes.
That means many cases will be missed, while daily case counts and test positivity rates – the percentage of tests that come back positive – don’t reflect what’s happening in the general population.