There’s a common saying ,”the numbers don’t lie,” but is that true? Well, kinda. If you’re tracking stats consistently you’ve got an objective dataset that in an of itself doesn’t lie. But what you do with that data or how you arrive at that data can be manipulated in a way to tell the narrative that you’re wanting to tell. You can tell a story from true data that doesn’t hold as true when you look at it in a broader context.
Let’s look at an example with the current Covd-19 Pandemic. Here’s a Tweet from Andy Slavitt on May 2:
A couple points first. I don’t have the exact data sources that Mr. Slavitt was using for his numbers, so the exact daily count that I refer to in a moment won’t match. My sources were Worldometer for USA and the New York State Department of Health Covid-19 Tracker for New York. With that out of the way, let’s take a look at the Tweet and the data itself.
First, let’s talk about the truth of the data. In a 7-day period the number of new cases in the USA outside of New York did increase, per his data source, by 17%. And at that growth rate we would see over 50,000 new cases by Memorial Day. The math adds up in and of itself. But why choose those two days in isolation? What happens if we look at other 7 day changes right around that time? Let’s take a look at this table:
Again, my data source is probably a little different than Mr. Slavitt, so the exact numbers won’t match. But let’s jump forward a couple days to the 7-day period ending 5/3. If we use that date then the case numbers outside of New York actually grew by even more (19%) than the seven days he referenced. If we use that date and percentage growth than we’d have even more than 50,000 new cases by Memorial Day.
The problem with either of these two dates is that it’s not looking at those individual days in context. Using this same approach we could actually forecast the opposite effect. The seven days ending 4/30 saw a drop in cases outside NY by -6.2%. So using that number we’d project just over 20,000 new daily cases by Memorial Day. I used the exact same logic and a date only two day prior to produce a result that was 60% lower. That’s the danger of using such a small data point out of context to make proclamations. You really need to look at the context and a bigger range of days to get a better feel for how things are going.
I think a more useful thing to do is compare the seven day average between two days. That will do a better job normalizing the numbers. On 4/29 the average was 24,128 outside NY and it was 25,463 on 5/5. That’s a 5.5% growth in a week. So, again, using just that logic and a small dataset that projects new daily cases around 30,000 at Memorial Day.
But what does the trend actually look like? Here’s a chart to help show the numbers:
For the last three days the USA has seen daily cases outside NY at or below the seven day average. Part of the reason that the seven day trend is going up is the spike in cases on 5/1. That number will make the average grow, for sure. But a very small downward trend might be starting now. We will see soon.
So, what’s the takeaway from all this? Simply this. It’s nearly impossible to know what the future will bring with this virus. If you want to paint a rosy picture you can find the data to do that. If you can only see doom and gloom you can find the data to support that opinion.
My personal read on the data in a broader sense is that things will start to greatly improve between now and Memorial Day. I am generally an optimist, so this is my default position. But I also think the data is starting to point that direction. Most states are seeing an overall downward trend in most every key metric. Time will tell.
Stay smart and stay safe everyone. This too shall pass. Hopefully soon.
