New positivity

This graph presented Aug. 19 by Indiana State Health Commissioner Dr. Kris Box shows Indiana’s positivity rate over time as calculate by dividing all positive test results by all tests administered, a calculation that gives slightly slower rate than the method Indiana has been crunching up until now. The state will add this new positivity calculation to its state dashboard, while continuing its previous method, too.

INDIANAPOLIS — What’s Indiana’s COVID-19 positivity rate?

Well, that depends on which numbers you’re using to calculate it.

On Aug. 19, Indiana State Health Commissioner Dr. Kris Box announced that the state would soon be providing a second positivity rate calculation to the public that differs slightly from the one the state has been using so far during the pandemic.

Until now Indiana has been looking at positivity — the percentage of tests that are returned with a positive result — as a measure of how many unique individuals tested positive per unique individuals tested.

As of Aug. 19, Indiana’s all-time positivity rate using that calculation sits at 8.8%, with a recent seven-day average of 7.7%.

The lowest positivity rate the state had hit was a seven-day average of 5% in late June and health officials have stated they would like to see rates lower than 5% in the state. A low rate would indicate that Indiana has a robust testing total and it is helping to find relatively few cases.

However, there are other ways to calculate positivity and no one method is standardized across the U.S., with no specific direction from the Centers for Disease Control and Prevention on what method is best. Therefore, different states calculate the percentages differently.

On Aug. 19, Box announced that the state would add a second calculation to its statewide dashboard, one that will fall in line with the way many other states are calculating positivity, giving Indiana the ability to better compare how it shapes up against its peers.

Indiana will not stop calculating and displaying its positivity rate in the old method, but will simply add the new method as a secondary feature.

“We will calculate the percent of positivity based on the total number of positive tests divided by the total number of tests. This will give us additional insight into our community spread and allow us to compare this metric to other states who are also using this method,” Box said.

“We want to be transparent and share as much data as possible,” Box added later. “Adding this additional calculation will allow us to more accurately compare ourselves to other states.”

Box noted that regardless of which measure is used to calculate the rate, the overall trend seen over time will look substantially similar on both charts.

“What’s important to note is that the positivity trend is the same for both methods, whether the percent of positivity is decreasing, increasing or staying the same remains consistent,” Box said.

In the end, positivity in itself is a contextual metric that helps explain changes in daily case counts.

Case counts can go up or down depending on how much testing is being done, so positivity is a control that helps explain whether the raw totals that are being recorded on a daily or weekly basis are simply a sign of bigger testing numbers or a sign that maybe the virus has come back strong.

For example, finding 1,000 cases on 10,000 tests, 10% positivity, tells a different story about overall prevalence of the virus than identifying 1,000 cases on 25,000 tests, a 4% rate.

Due to numerous questions about this change, here’s a detailed explanation about three different methods of calculating positivity, what their strengths and weaknesses are and how they are different from one another.

But first, a quick refresher on math terminology and fractions:

In division, the numerator is the top number and the denominator is the bottom. When calculating fractions and percentages, the result you’ll get will be higher whenever your numerator grows in comparison to your denominator. Inversely, the number will shrink if your denominator gets bigger than your numerator.

For example, ½ gives you 0.5, while 3/2 is 1.5.

When both parts are changing at the same time, bigger results will occur when the numerator increases at a larger rate than the denominator.

For example, 43/100 is 0.43, but if you triple the numerator but double the denominator, 129/200, you get 0.645.

Now, on to the explanations:

Method 1: Unique positives/unique tests

This is the calculation Indiana has been using thus far in the pandemic, dividing the total number of unique Hoosiers who test positive by the number of unique Hoosiers tested.

To date, as stated above, Indiana has an all-time positivity rate of 8.8% using this metric.

The main flaw in this method of calculation is that it can produce artificially high rates because it does not take into account retests.

When someone is tested for the first time they are logged as a unique test. But if that first test is negative and they go back for a second or third or beyond test, those subsequent tests would not be logged, because it is the same person and they’ve already been counted.

Box explained Aug. 19 that it wasn’t a major issue early on, because testing was limited and few people were taking more than one COVID-19 test.

“That means if someone is tested repeatedly, we only counted that person once. This was the right approach at the time because early on we weren’t seeing people tested multiple times. This has changed,” Box said.

The problem with this method is that if a person tests positive after their initial test, the state would then log that result as one unique positive, but it would not be reflected as a new test, therefore increasing the numerator of the equation but not the denominator, leading to a larger percentage.

As retests have become more common, this rate has shown to be artificially high because of the interaction described above.

Method 2: Unique positives/total tests

This calculation became possible as of three weeks ago, when Indiana began reporting daily the total number of tests it was administering.

This is the calculation being used internally at KPC Media Group and reported in daily update stories to our readers in northeast Indiana.

By dividing the unique positives — the actual number of people who have been infected — by all tests, this rate captures a truer picture of positivity by taking all retests into account.

Doing this math eliminates the problem described in the first method, because even if a person tests negative on their first test — it is counted as one test, zero positives — if they later test positive on their second test it is then counted as one test, one positive instead of zero tests, one positive.

Using this calculation, the all-time positivity rate registers 2 percentage points lower at 6.8%, because the denominator, total tests, is larger than it is when using only unique tests.

Compared to the other methods, this version will give the lowest rate as an output.

To date, 934,033 unique Hoosiers have been tested with a total of 1,202,015 total tests administered. That means, of all tests done, 267,982 have been retests among those 934,033 individual Hoosiers.

Method 3: Total positives/total tests

Some people who test positive for COVID-19 will be tested multiple times and will register positive multiple times.

While the state reports its case numbers on its dashboard as unique positives — actual people who have been identified with COVID-19 totaling 82,336 to date — Indiana also has data for total positive test results that would include any multiple results.

Since health officials are not aware of any people getting reinfected — getting sick a second time after recovering from the illness a first time — the difference between unique positives and total positives would reflect only how many duplicate positives have resulted from retests.

This could occur if a person who gets sick is being tested again to see if their body has cleared the virus or to find out whether they are COVID-free in order to transfer into a rehab or nursing home facility or maybe be cleared to go back to sensitive jobs such as health care or nursing care where employers want to know for certain their worker is no longer carrying the active virus.

As of Aug. 19, Indiana hasn’t started displaying totals for all positive tests results, but Box presented a chart in the statewide news conference showing how this method would shape up.

While the chart presented didn’t have an all-time positivity rate calculated this way, it showed that as of Aug. 11, the seven-day average was 6.5%, 1.2 percentage points lower than the 7.7% average shown via the first method described in this article.

Because the addition of all tests would increase the numerator by some amount, the rate calculated via this method will likely sit somewhere higher than unique positives/all tests but under unique positives/unique tests.

While capturing all positive results, even those done on retests of people already known to be sick, may not have much relevance to the overall extent of the virus’ reach, the main benefit of this calculation is simply that many other states are using this metric, thus allowing Indiana to have better comparisons to other states.

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