As Canada slowly reopens, here are six coronavirus numbers to keep an eye on

Click to play video: 'Testing for COVID-19 in a West Island ‘Hot Zone’' Testing for COVID-19 in a West Island ‘Hot Zone’
WATCH ABOVE: Testing for COVID-19 in a West Island ‘Hot Zone’ – May 14, 2020

The novel coronavirus is an invisible enemy. One of our main weapons is an endless stream of data, but it can often seem confusing.

As society cautiously reopens, how would we know if we were keeping it under control? Here are six numbers to keep a close eye on.

What percentage of tests are positive

Why does that number — ‘test positivity’ — matter?

If too high a number of tests are positive, it suggests that there are a large number of cases in the community that aren’t being found.

If there are, it raises the question: Are we testing enough, in relation to the scale of the problem?

The World Health Organization looks for a number under 10 per cent, though Global News has talked to experts who say that number is arbitrary, and set too low.

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(Whether a place is testing enough is crucial to whether it can afford to reopen: with such a high-stakes decision, the more we know the better.)

Applied to Canada, the graph below seems reassuring, except for Quebec, where test positivity rates have stayed stubbornly above 15 per cent for nearly a month.

READ MORE: As Canada reopens, are we ready for a ‘second wave’ of coronavirus infection?

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How testing rates are changing

In early April Ontario, Canada’s second-worst-hit province after Quebec, had the country’s lowest testing rate.

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In this case, the question is: Are the worst-hit provinces testing enough?

As you can see, that’s changed dramatically, perhaps in part because of pressure from Premier Doug Ford. In the past week, Ontario has had the highest testing rate among all provinces. (Only high-population provinces are shown below.)

READ MORE: Room for hope — but also warning — in Canada’s flattening coronavirus curve

How fast does it take for cases to double?

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Given that we know that too fast an increase in cases would overwhelm our ability to cope with them, it’s important to know how fast they are growing. 

The chart below shows how fast confirmed cases are growing, by depicting how long it takes them to double in any given province.

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As you can see, it’s between a week and two weeks for most provinces, other than in Quebec.

Please note that the chart below is a ‘logarithmic chart: the vertical axis expands at an accelerating rate.

READ MORE: How many coronavirus cases are really out there? Why deaths may offer a clue

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How to look at Canada’s coronavirus death data

What can we learn by looking at Canada’s national coronavirus death toll? It shows that we’re flattening the most important curve, which is how many Canadians the virus kills. 

As you can see, there’s a lot of daily variation in coronavirus death. It can get distracting if you want to understand trends, so it’s probably more helpful to look at the solid line in the chart that shows a 7-day average.

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The line starts flattening in mid-April, about a month after Canada started going into lockdown: this makes sense, since people who die of coronavirus generally die about three or four weeks after infection. So it’s helpful to think about the data as backdated by a month or so.

Also, data about death can unlock the door to learning some of the pandemic’s secrets.

As we learn more about the coronavirus, we are getting closer to figuring out what the real death rate is: it’s challenging at the moment, because we don’t know how many people truly have the disease. One study estimated it as .37 per cent, which means there may be roughly 300 Canadians with coronavirus for every one who dies of it. That works out to about a million people. For that to be true, there would have to be a very large number of asymptomatic people.

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READ MORE: What the coronavirus reproduction number is, and why we should keep an eye on it

Does the reproduction number start with a decimal?

Is a pandemic getting worse, getting better or staying the same? Epidemiologists tell us to look at something called the ‘reproduction number,’ or ‘R number,’ to get an idea. The math of how it’s calculated is complex, but the concept is very simple: on average, how many other people does someone with coronavirus infect?

We want to see an R number as far below 1 as possible.

In mid-March, as Canada started to shut down schools and businesses, the R number was a potentially catastrophic 2.8. That had the potential for an out-of-control pandemic: if one person on average infects 2.8 people, and each of those people infected 2.8 more people, hospitals would quickly have been overwhelmed.

Now, as you can see, the R number is around .8, which means the outbreak is shrinking, though not as quickly as we would like.

READ MORE: Wider testing, surveillance needed to catch asymptomatic COVID-19 cases: experts

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Infections more common in the old – or are they?

The chart below has changed very little since we first started updating it in March. In general, the older the age group, the higher the positive test rate. Over-80s have far more than their share of infections, and teens and children far less. Or so it would seem.

But what if it pointed toward something else: cases in the young that aren’t being detected?

A German study published in early May suggests another interpretation. In that study, over 900 randomly selected people of all ages were tested for coronavirus.

“The infection rate in children, adults and elderly is very similar and is apparently not dependent on age,” says Prof. Hendrik Streeck of the University of Bonn.

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So another interpretation of the graph is that it shows how we are more aware of coronavirus cases in the middle-aged and elderly, and that the reason we’re more aware of them is that they experience more severe effects, and are more likely to seek out medical attention and testing. Conversely, many younger people are positive, but show no symptoms.

(Among crew members with positive tests on the aircraft carrier USS Theodore Roosevelt, a group that’s younger than average, a majority were asymptomatic.)

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