Measuring success: what metrics are used in the fight to flatten the coronavirus curve?.

WATCH: Where on the curve will Canada struggle to keep up?

For several months, health officials around the world have been touting various tools for combatting the novel coronavirus.

As cases continue to rise in Canada, the term “flattening the curve” has been advertised as a way for individuals to limit transmission to prevent the health care system from becoming overwhelmed.

Social distancing, self-isolation and travel restrictions are lauded as crucial components of reducing and preventing further spread of COVID-19, but what key metrics can be measured in the fight to flatten Canada’s curve?

Alon Vaisman, an infectious diseases physician at Toronto General Hospital, said the main variables public health officials will be looking for are the number of new cases, deaths, recoveries and how these numbers are changing from day-to-day.

One of the main ways to measure that, he said, is by looking at the number of cases that have doubled each day.

“If you’re seeing a doubling of the curve of increasing cases, that could be indicative of an outbreak that’s very hard to control or even lost control,” he said.

He noted that these numbers, however effective, are “not set in stone, though.” The doubling rate has to be calculated against the incubation period of the disease.

The novel coronavirus has an incubation of up to 14 days, which means the government wouldn’t see the full effects of any of their interventions, like social distancing for example, until two weeks later.

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Health Canada was unable to respond to requests for comment in time for publication.

Measuring the slope of Canada’s curve

Through measuring the rate of cases, infection control epidemiologist Colin Furness said the government can make decisions on how to best flatten the curve.

“The steeper the curve, the more cases we’re getting in … the more scared we should be,” he said. “The more horizontal, the flatter the shape of the curve, the better.”

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Furness, who has been tracking the curve of Canada’s COVID-19 slope on his own EpiModel, said during the initial outbreak of the virus, cases were doubling every four days.

Weeks later, they were doubling every three days. Shortly after that, he said cases began doubling two and a half times every three days.

The curve was getting steeper.

Shortly after that, Furness said the government began implementing social distancing — and the impact got his attention.

“It calmed right down,” Furness said of the curve. It went down to about 1.7 every three days, which is great. It got almost to the point of going back to doubling every four days, which is great.”

But on Monday, he said cases spiked again. The infectious disease specialist said the government will make informed decisions based on what they can deduce from the sudden increase.

The measure of success, Furness said, will be when cases stop doubling and the country stops getting new cases, thereby flattening the slope.

He added that Canadians should be mindful that just because a curve decreases, doesn’t mean they should expect the government to scale back preventative measures.

“If cases are still increasing at all and we let those up, it’s just going to skyrocket again. Just like with a fire, you don’t stop when the fire’s almost out because you know that it’ll just pick up again,” he said.

Subject to change

According to Furness, “these things can really change on a dime,” and urged Canadians not to panic every time they see a sudden jump in confirmed COVID-19 cases.

If health care workers get infected en masse, or if there’s an institutional outbreak in, for example, long-term care homes or prisons, spikes can occur that are based on local phenomena, he said.

“Whenever you see a spike, your next question should be, who, where was that, and why?” Furness said. “A spike can mean that all of our social distancing measures failed or it could mean that one person managed to infect 50 other people just ’cause.”

Asymptomatic transmission, he said, also raises concerns that the data may be skewed.

The government’s approach to doing testing is predicated on the assumption that it can identify who is at risk and who should be tested. If infected Canadians are unknowingly passing the virus to healthy people, the curve will reflect the number of people tested, rather than the number of people sick.

© 2020 Global News, a division of Corus Entertainment Inc.

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