How will we know when we’ve turned the COVID-19 corner?

Here’s the COVID-19 number that I’m watching.
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Cutting to the chase, I’ve concluded that the most reliable number being reported is the number of COVID-19 related “Daily New Deaths”.

According to Worldometers – the best data aggregation site that I’ve found so far – there have been 275 COVID-19 related deaths in the U.S. so far.

image

That chart looks exponentially ominous … but remember that we’re looking at relatively small numbers.

Note: Over 60% of the fatalities are clustered in 3 states WA, NY, CA — with half of those in Washington.

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So, I think it’s more useful to look at “Daily New Deaths” …. if that number keeps going up then, by definition, we haven’t turned the corner.

When that number starts trending down then, by definition, we have turned the corner.

Here’s what Worldometers is reporting on “Daily New Deaths” for the past 3 days: 41, 57, 49.

image

Don’t get too excited about yesterday’s drop in fatalities … again, keep in mind that we’re dealing with small numbers.

In the unlikely case that the number stays around 50, then it’s time to celebrate.

Keep in mind that during flu season, we rack up about 250 flu-related deaths per day.

Bottom line: If you want to know if we’re starting to turn the corner, keep your eye on the number of COVID-19 related “Daily New Deaths”.

Choose the level of aggregation based on your specific interest … world, nation or state.

Note: I’ll be focusing on the U.S. national number … and the national number less the 3 state hot spots.

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Why “Daily New Deaths”?

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Why have I centered on Daily New Deaths (DND)  as my key metric?

First,  saving lives is our paramount objective, right?  If yes, it should be our focus metric.

Second, I think that most other metrics that are being bandied about are quite problematic.

Counting deaths — while a bit macabre — is a more reliable process than counting, say, the number of infected people.

Sure, I’d like to know the number of people infected with COVID-19.

But, unless everybody — or at lest a large statistical sample — is tested, that number is subject to lots of statistical issues.

Most notably, who is being tested and who isn’t? What about the asymptomatic “hidden carriers”? What are the criteria for confirming a COVID infection? How to standardize the reporting processes? How to keep governmental units from fudging the numbers?

For example, if testing increases, then confirmed cases goes up.

Is that an indication of more virus spread or just a reflection of more testing?

I sure can’t tell.

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Again, counting fatalities is probably the most reliable metric.

Fatalities are discrete events – so they’re countable.

Still, even deaths may have some counting imperfections.

For example, many non-hospitalized people die and are buried without autopsies.  Some may be uncounted COVID victims.

On the other hand, some people may die and be diagnosed with COVID infections. That doesn’t necessarily mean that COVID killed them.  That’s especially true with COVID since it’s  most deadly for people with other health problems.

And, COVID deaths are a function of two drivers: the incidence of the virus … and, the nature, level and timing of therapeutic healthcare.

Said differently, more effective therapeutic healthcare will dampen the death toll.

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Why not the death rate?

Simple: If you divide a reasonably reliable number (the number of deaths) by an unreliable number (the number of confirmed cases), you get an unreliable number (deaths as a percentage of cases).

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Bottom line: I still conclude that “Daily New Deaths” is the number we should be watching.

If it stays stable or shows a consistent downward trend, then we’ll know we’ve turned the corner.

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Follow on Twitter @KenHoma

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71 Responses to “How will we know when we’ve turned the COVID-19 corner?”

  1. ST Says:

    It’s an interesting metric. As morbid as it sounds, I would also like to see the same mortality numbers based on age brackets, particularly 80+, 70+, <70. It would also be helpful to see how many fatalities in the <70 bracket had contributing factors like diabetes, history of cardio or pulmonary issues, cystic fibrosis, etc. in order to get a clearer picture of risk, although it potentially muddies the data (what is included and what is not and how do you determine so). I clicked on your worldometers link and it provided some of that information, but universally.

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