VANCOUVER \u0026mdash\u003B When Caroline Colijn sees the daily numbers of new cases of COVID\u002D19 in Canada, she looks for certain things.
But when they do, if effective, they should begin to appear as declines in the new number of cases relative to the days before and, ultimately, no new cases.
But the challenge for both mathematicians and the federal government is a lack of data in some cases — and what Colijn called “noisy” data skewed by many factors in others — making it hard to predict the course of the disease in Canada. First, we’re still learning about disease transmission and behaviour. Second, confirmed cases reflect the recent past, not the present, because of the virus’s incubation period. And third, testing protocols have shifted and many people who have symptoms consistent with COVID-19 will never be tested, meaning modellers don’t have accurate numbers to work with.
In reality, we’re somewhere in the middle, where measures like social distancing and self-isolation will be key to flattening the curve, she said.
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