As Memorial Day weekend opened, North Carolinians were greeted with concerning news. Headlines included:

At his press conference Tuesday after Memorial Day, Gov. Cooper told everyone “we need to stay alert: over the weekend we saw our highest one-day increase in positive cases and our highest day of hospitalizations yet.”

This news was first announced to the media in an NC Department of Health and Human Services press release on Saturday, May 23, entitled “NCDHHS Reports Highest One-Day Increase of COVID-19 Positive Tests.” It began:

The North Carolina Department of Health and Human Services (NCDHHS) is reporting the state’s highest one-day number of laboratory-confirmed COVID-19 cases with 1,107 cases reported.

This is a notable and concerning increase. As we head into a holiday weekend, please practice the three Ws – wear a face covering, wait six feet apart, and wash your hands frequently. When it comes to our health, we need to work together to protect our families, friends and neighbors,” said NCDHHS Secretary Mandy Cohen.

As you see, DHHS considered this highest one-day increase in cases unusual. It’s “notable and concerning,” Cohen pointed out. That sounded like bad news, and media treated it as such.

But DHHS didn’t want this increase in cases to sound merely “notable and concerning.” It had to sound baffling — a mystery only to be solved by state experts. As it stated,

NCDHHS epidemiologists are analyzing the data to determine if there were any significant contributing factors.

Oh dear. “Significant contributing factors” could be anything!

What if too many people aren’t choosing to “Just wear the stupid mask,” in the words of a priggish N&O editorial? What if the virus is no respecter of social distancing? Or was it the churches, even though we tried to stop them? What if we opened state parks too soon?

A math problem

How about this: What if it was the denominator? Let me explain.

A person does not wake up with a laboratory-confirmed case of COVID-19. A person may or may not have a case of COVID-19, but a laboratory-confirmed case must first be (hence the term) confirmed by a testing laboratory. Which means they must be tested.

The Cooper administration has, in fact, made a big deal about having more testing. Cooper even specifically declaring having a “leveling or decreased trajectory in percent of tests returning positive over 14 days” one of his “key metrics” of progress.

Percent of tests returning positive? Over 14 days? There’s the thing. We can’t tell the significance of a raw number of cases from a single day’s batch of tests. For proper comparisons, it’s just as important to know how many people were tested, and what is the trend over time. Using an interval such as 14 days helps smooth out any one-day wrinkle in the data.

To find “the percent of tests returning positive” requires math. The raw number of tests returning positive is the numerator. The total number of tests is the denominator. Multiply the result by 100 to get the percent of tests returning positive.

What DHHS told the media in the May 23 release: there were 1,107 new cases, and that was the “highest one-day number of laboratory-confirmed COVID-19 cases.” The numerator was 1,107.

What DHHS didn’t tell the media: how many tests were in that batch. What was the denominator?

As it turns out, the denominator — the number of tests that day — was also the highest one-day number of tests. It was the highest by far. At 26,358 tests, it was over twice the previous testing high (13,042 on May 21, for which 778 returned positive). Data source here.

Even more importantly, the percent of tests returning positive the 14 days ending May 23 — a metric set by the Cooper administration, rememberhit a new low. It was then 5.8 percent. As of today, it is 5.7 percent.

Unanswered (unasked) questions

Wait, a new low? Why haven’t we heard about that? Good question.

Why did DHHS choose to focus exclusively on the new high in new cases, and why, in his post-Memorial Day press conference, did Cooper choose to repeat about the “highest one-day increase in positive cases” without telling the rest of the story?

Also, why are they ignoring a continuing good trend in one of their own metrics?