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LWC Shortcast: How was Alberta’s coronavirus modelling so far off? Expert Caroline Colijn explains

UPDATE (May 11): We’ve included more on the undetected coronavirus cases below.

If you were anything like us, you took a look at the 6,000+ coronavirus in Alberta today, at the presumed mid-May peak, and compare it with that initial modelling done in early April.

In a televised address April 7, Alberta Premier Jason Kenney said that under a probable scenario, we expected 800,000 COVID-19 cases, both confirmed and undetected in Alberta by September.

6,000 now vs 800,000 in a few months. Right now we’re going up by 50 to 75 per day. Even on the high side we’d only add 9,000 more cases by then.

How does that happen? Is it really the physical distancing, the hand washing – ALL the public health measures?

We sought out some answers.

We spoke with Caroline Colijn, a researcher in the Simon Fraser University Department of Mathematics. She’s an expert on the connection between math and epidemiology and infectious disease. Colijn is also an active participant in British Columbia’s COVID-19 modelling.

While it’s not exactly a shortcast, it’s a curious conversation that we hope answers that question: How was Alberta’s modelling so far off?

NOTE: Colijn did get back to us on the question of social engineering and its part in developing models (35:00). Essentially, we asked: Are models built to scare people into compliance with rules?

She said it’s absolutely not part of the modelling that’s been done in BC. She also said that there’s been no government influence on how the modelling was constructed in that province.

Colijn said that what may throw all this off is what date the initial r0 inputs were used. If it was January or February put into a late March, early April model, that would have a significant impact on the projections.

More on undetected coronavirus cases

Some fantastic response to this audio story, and through it, the big question is, how are we calculating undetected cases?

Short answer: There’s no specific calculation yet.

We asked University of British Columbia mathematian and epidemiology and infectious disease modelling expert Daniel Coombs about it.

Here’s a portion of his email response:

“We will not know until we have very large scale randomized serology tests. I have been guessing a factor 5 to 10 since this started and have yet to see anything that indicates I am wrong about that.

I suspect that under-reporting in the over 70 age group may be smaller (say a factor of two) due to generally higher vigilance and more serious symptoms. Possibly a factor of ten (or higher) in the 18-30 group.

In kids, it is even harder to understand what is going on.

Very, very roughly, and with a million caveats: if the infection fatality rate is 0.1% in adults 18-70, then because we have had ~10 deaths in that group in BC, that points to very roughly 10,000 total infections. Which is in the range of a 5-10 multiplier above detected cases.”