Pandemic data derivation


NICK EICHER, HOST: It’s Tuesday the 25th of August, 2020. Glad to have you along for today’s edition of The World and Everything in It. Good morning, I’m Nick Eicher.

MARY REICHARD, HOST: And I’m Mary Reichard. First up: A special report on the numbers behind the pandemic.

Since March, health officials around the world have been talking about COVID-19 statistics. Case counts, hospitalizations, and mortality rates.

EICHER: But all those numbers can be hard to interpret. So we asked two WORLD reporters to help clear up some of the confusion.

ABC: Florida now surpassing 100,000 cases…

GMA: We are up to 14 million cases globally. 

WOLF: There’s been dramatic increase in hospitalizations.. 

SOT: The U.S. has now conducted 28 million COVID-19 tests.

ABC: The United States is reporting the highest number of deaths in a single day… nearly 1,500. 

SARAH SCHWEINSBERG, REPORTER: COVID-19 statistics. These are the numbers that inform lockdowns, travel restrictions, and mask policies.

ANNA JOHANSEN, REPORTER: And to debate policies, it’s important to understand where these stats come from and what they mean. 

SCHWEINSBERG: I’m Sarah Schweinsberg.

JOHANSEN: And I’m Anna Johansen.

SCHWEINSBERG: Whip out your calculators and buckle your seatbelts, folks, because we’re going to take you through a whole lot of ways to measure a pandemic. 

JOHANSEN: We aren’t going to talk about the numbers themselves. Instead, we’re going to explain where some of those stats come from. So let’s dive into our first set of data: Positive case counts. That’s the number we hear about the most.

SCHWEINSBERG: This is the total number of people who have tested positive for COVID-19. As of yesterday morning, the Centers for Disease Control and Prevention reported that more than 5-and-a-half million Americans have tested positive for the virus. 

JOHANSEN: So how does the CDC actually track these positive case numbers? 

It starts, as you probably know, with testing. 

There are three types of tests. Two diagnose an active case of COVID-19: Molecular tests and antigen tests. A molecular test is the most precise. It actually identifies the genetic material of COVID-19. It’s hard to fool.

Dr. Dominik Mertz is an infectious disease professor at McMaster University. Here’s how he describes molecular tests.

MERTZ: This is considered the gold standard because it’s the most sensitive test that we have. Sensitive means that it’s most likely to pick up the virus and identify that the virus is there.

SCHWEINSBERG: The second diagnostic test is an antigen test, and it looks for specific proteins on the surface of the virus. It’s also known as a rapid test because you typically get results back within an hour.

But it’s not as accurate as a molecular test. It tends to miss cases it should have caught. 

JOHANSEN: And Dr. Mertz says not even molecular tests, the gold standard, hit the mark every time.

MERTZ: We had quite disappointing numbers early on where this sensitivity was reported to be only about 70 percent. So that will mean you will have missed 30 percent of people who in fact, should have had a positive test. 

Over the past few months, the tests have gotten more precise. Dr. Mertz says the molecular tests are now up to about 90 percent accuracy.

SCHWEINSBERG: The third kind of test isn’t a diagnostic. It’s an antibody test, based on a blood sample, and it checks to see if you’ve had COVID-19 in the past.

But antibody tests aren’t always accurate either. Here’s Dr. Amesh Adalja. He’s a senior scholar at the Johns Hopkins University Center for Health Security. 

ADALJA: Some of the early antibody tests had a lot of cross reactivity and false positives. And the antibody test by definition is going to be looking backwards. So it’s not the best way to plan your response or to think about where you are in terms of the pandemic.

JOHANSEN: Now, only molecular and antigen tests are used to log new positive coronavirus cases. That’s because they identify patients who have the virus right now. But at the beginning of the pandemic, some antibody tests were being used to log active cases—even though that’s not what they’re designed for.

SCHWEINSBERG: But Dr. Adalja says early on, health officials also grappled with false negatives from molecular tests…and limited test availability. So he says the over-counting on some fronts and undercounting on others…canceled each other out. 

ADALJA: There is always going to be adjustments up and down during a pandemic, when you look at the way the data is handled from health systems. That’s just that’s just to be expected.

JOHANSEN: The longer the pandemic continues, the more testing capacity states have. Early on, only people with severe symptoms or a recent travel history could get tested. Now, it’s anyone with a mild cough. So, many people wonder, are cases rising because we’re testing more people?

SCHWEINSBERG: We asked a couple of biostatisticians about that. Christopher Lindsell teaches biostatistics at Vanderbilt University. He says yes and no.

LINDSELL: When you test more, you will find more cases. But that doesn’t mean that the case rate is going up or going down. We have to look at the numbers as a proportion or as a ratio of the general population.

In other words, positive case count numbers can sound like a state is doing poorly or relatively well until you consider how many people have been tested overall. Positive case counts have to be put into context.

That context is called percentage positivity. It measures the ratio of people who tested positive for COVID-19 compared to the total number of people who were tested. That gives you an idea of what proportion of the population has COVID-19. 

JOHANSEN: So for instance, at the beginning of July, Florida tested about 525,000 people in one week. Out of those, nearly 80,000 were positive. That’s about 15 percent. So in July, Florida had a percentage positivity rate of nearly 15 percent.

Yesterday the state reported its case positivity rate has now dropped to below 5 percent. That means fewer people are actually getting the virus. And when a positivity rate stays below 5 percent for two weeks, health experts consider the virus under control. 

SCHWEINSBERG: OK, we’ve covered where case counts come from—what about COVID-19 deaths? Those numbers come from death certificates. Each one of those lists a primary cause of death and a secondary cause.

The primary cause is the disease or event that directly led to death. The secondary cause is either a complication or a contributing factor. 

And that’s where counting COVID-19 deaths can get murky. What’s the difference between dying with COVID-19 and dying from COVID-19? 

JOHANSEN: Let’s say someone with a pre-existing heart condition has COVID-19 and then dies of a heart attack. Here COVID-19 is listed as a secondary cause of death because it contributed to the heart attack. So Dr. Amesh Adalja from Johns Hopkins says it would be counted as a COVID-19 death. 

ADALJA: So you could have a stroke and that stroke could be caused by COVID-19. Or you could have COVID-19 be on a, be on a ventilator and then die from a bacterial pneumonia, where COVID-19 would be a true cause of death because it contributed to that. So what we do is you have to kind of adjudicate what role COVID-19 played in that person’s death.

SCHWEINSBERG: So when would a medical examiner not list COVID-19 on the death certificate? Say someone dies in a car accident and in the autopsy, the medical examiner discovers the car accident victim also had COVID-19. Well, COVID-19 had nothing to do with the car accident. So it wouldn’t be listed and the person wouldn’t be counted as a COVID-19 casualty. 

JOHANSEN: But wait, doesn’t the federal government reimburse hospitals more money if someone dies of COVID-19? How do we know that doesn’t motivate doctors to wrongly attribute deaths to the coronavirus? There have been stories of families who say their loved ones were counted as COVID-19 victims without a confirmed diagnosis. So are doctors or hospitals inflating the fatalities?

SCHWEINSBERG: Dr. Adalja says it’s unlikely. Why? Because this isn’t the first time the federal government has offered hospitals more money for caring for certain patients.

ADALJA: So this happened with Ebola as well that there often is extra compensation for hospitals. And I don’t think it creates any kind of incentive to over-classify COVID-19 patients because there are strict diagnostic tests and criteria that we use to decide whether that is the case. 

So if there are some gray areas around COVID-19 deaths, how can we be sure the death count is accurate? This is where another statistic can be helpful. It’s called the excess mortality rate. 

JOHANSEN: The excess mortality rate is the difference between the actual number of deaths in a time period and the expected number of deaths in the same time period. So death counts this month are compared with death counts from this month last year. It’s a way to cross check the data.

SCHWEINSBERG: Before 2020, COVID-19 wasn’t on the scene. Dr. Ali Mokdad teaches health metrics and epidemiology at the University of Washington. He says it’s possible to compare this year’s number of deaths to last year and assume that additional deaths this year are mostly a result of the coronavirus.

MOKDAD: We will revise this mortality later on once the data becomes available. And we do this with every other event. We did it with SARS, we did it with MERS. And that’s typically what all countries will do when they revise their estimates up and down.

JOHANSEN: For instance, in New York City, data published earlier this year show just over 25,000 excess deaths between March and June. That number is close to the 24,000 confirmed and suspected COVID-19 deaths in the city so far. 

SCHWEINSBERG: But the excess mortality rate doesn’t take into account additional suicides because of isolation or people who died because they stayed away from hospitals for fear of the virus. 

Dr. Amesh Adalja of Johns Hopkins says death certificates can help identify how many of the excess deaths in the city were a result of these causes and not COVID. 

ADALJA: This has to be part of what we think of when we’re thinking of the total impact of this pandemic.

JOHANSEN: Okay, but what about the people who’ve had COVID-19 and recovered? Why don’t we hear more about them?

SCHWEINSBERG: Well, one reason—in a pandemic, the media and leaders tend to focus on the sick and dying. Not the people out of the woods. And Dr. Adalja says states aren’t actually tracking COVID-19 patients. Thirty days after a positive test, if you haven’t died, states consider you recovered. 

ADALJA: For a state when they talk about recovered patients, what they’re referring to is just a period of time that passes after your positive tests, and then you just move to the recovered column. 

So states don’t really know if people are fully recovered from the virus. Dr. Adalja says that’s why he doesn’t really look at recovery rates. 

ADALJA: It doesn’t really give you any kind of granular look at what’s going on with those people. So a person might have recovered, but they’re still having difficulties with concentrating, maybe they’re still short of breath. So it’s, it’s not a good number just to look at it. 

JOHANSEN: So with all the data points we have, which ones are the most important? 

Well, that depends on who you ask…but all of the experts we spoke with agreed on one thing: It’s never helpful to look at one statistic isolated from the others. Chris Lindsell from Vanderbilt was pretty adamant about that.

LINDSELL: I think just counting the absolute number of positives is absolutely the wrong thing to do.

SCHWEINSBERG: We can’t just say, Florida has 590,000 cases and Illinois only has 214,000, so Illinois must be better than Florida.

Each data point tells only part of the story. 

For instance, Dr. Mertz of McMaster University says it’s important to combine case counts with hospitalization rates and mortality rates.

MERTZ: If those three are aligned, that that’s a very clear picture for you that it’s not only that you increase testing, you, you, you certainly have an increase in your community transmission.

JOHANSEN: There are dozens of other data points and questions to consider. And we don’t have time to get into them all today. But we will circle back to this topic very soon.

SCHWEINSBERG: And we’d love to hear from you. Let us know which questions we cleared up or didn’t…and let us know which questions you’d like us answer next time.

Reporting for WORLD, I’m Sarah Schweinsberg.

JOHANSEN: And I’m Anna Johansen.


(AP Photo/Riccardo De Luca) A medical worker wearing protective gear collects a swab from a passenger of a flight from Valencia, Spain, during a COVID-19 test, at Rome’s Ciampino airport, Wednesday, Aug. 19, 2020. 

WORLD Radio transcripts are created on a rush deadline. This text may not be in its final form and may be updated or revised in the future. Accuracy and availability may vary. The authoritative record of WORLD Radio programming is the audio record.

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4 comments on Pandemic data derivation

  1. Bob Thompson says:

    You need to talk about the most informative number: saves and deaths per 100,000 population. Break down by state or county or country. 1000 new cases in a state with 20 million people isn’t alarming compared to 1000 new cases in a state with two million people… Statista is a great resource for all manner of statistics.
    Bob Thompson

  2. Brenda Newell says:

    If an increase in the number of deaths in a state is an indication of COVID 19-caused deaths, what are some of those numbers for states other than New York and how do they compare to the increase in numbers of deaths in years when other viruses have caused a significant increase in deaths (for example, the flu strain that caused deaths in 2014)? Reports indicate that the epidemic was badly mishandled in New York City, making it a poor gauge of the impact of COVID-19 on mortality rates.

  3. Erin Goertz says:

    Thanks for this story! Will you explain the R0 number that is usually published with COVID-19 numbers?

  4. Barby says:

    I’d like to know more about age distribution of those affected and also about long term illness related to infection.

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