This episode was filmed on July 7, 2020.

For our latest COVID-19 coverage, you can find our full playlist in the description. [ ♪INTRO ]. Some people who get sick with COVID-19 are asymptomatic — meaning they don't feel any symptoms of the disease.

But the infection is still there. In a new study published in Nature Medicine last month, researchers compared what happens in the bodies of people with both symptomatic and asymptomatic infections. And it turns out that not having symptoms of COVID-19 doesn't mean your body isn't affected.

There's a lot we don't know about asymptomatic infections, including how common they are. We won't know the real number until all this is over, but some studies have estimated it might be around 35 to 40% of cases. So we really want to know what, if anything, happens to people in these situations.

In the new study, researchers in China looked at 37 people who tested positive for COVID-19 and had mild symptoms, as well as 37 who tested positive but didn't have any symptoms. And even if it wasn't obvious from the outside that the asymptomatic patients were sick, for most of them you could easily tell by looking at their lungs. Of the 37 patients in that group, 21 had abnormal chest CT scans, 11 of them with the ground-glass texture that's characteristic of COVID-19.

Even though they felt fine. The team also confirmed that people who are asymptomatic can still be shedding virus particles all over the place — in fact, they tended to do it for longer than people who did have symptoms. That's troubling, because we haven't ruled out the idea that asymptomatic people can spread the disease.

And a longer period of viral shedding could mean that not only are they contagious, they're contagious for longer. Or… not. You see, these particles aren't necessarily infectious.

The tests scientists use to detect viral shedding don't differentiate between broken-down bits of old virus in your snot and fully capable viruses that can go on to infect others. So that's one thing that could definitely use some more research. Because we need to pin down how infectious sick people are, whether they're symptomatic or not.

Beyond that, though, the team also looked at the immune responses of patients in both groups. Now, we don't yet know for sure if having COVID-19 makes you immune to getting it again. And even if it does, we don't know how long that immunity lasts.

But what the study found doesn't exactly build confidence. They found that three to four weeks after their initial exposure to the virus, most patients in both groups tested positive for antibodies to the virus. The study looked at several types of antibody, one of which was IgG, the most common kind — though, the symptomatic patients had much higher levels.

Then, eight weeks after they were all released from the hospital, that was still true — those who had been symptomatic had higher levels of IgG. But levels had fallen substantially in nearly all patients. In 12 of the patients who'd been asymptomatic, you couldn't detect these antibodies at all anymore.

The same was true for only four of the people who'd had symptoms. So, at least among these 74 people, some antibody levels seemed to drop within a few months of being infected, and in those who didn't have symptoms, they were more likely to drop below what we can detect. That's not super promising.

It's too early to say, though, that asymptomatic cases are at risk of getting infected again. We simply don't know if re-infection is a thing yet. And when it comes to immunity, these circulating antibodies aren't the whole story.

For example, we might also need to consider memory B cells. Those are the kind of immune cells that produce antibodies, and they can produce more in response to a repeat infection of the virus, even if the person didn't have many antibodies circulating in their blood when they were re-exposed. So even if asymptomatic patients do lose more of certain types of antibodies, we don't yet know what that means for their immunity.

The good news is that a new strategy is showing up that may help us detect more asymptomatic cases, and it's cheaper to boot. The workaround is... math. It's an approach you may have heard referred to as pooled or batch testing.

Say you have nasal swabs from 60 people you need to test. Two of them are positive, although you don't know that yet. Normally, you'd test each of those swabs individually, end up with two positive results, and you're done.

But you've just used up 60 tests. Another approach would be to pool the swabs together into, say, 12 groups of five, then test each group. Then you test each individual swab in any group that comes back positive.

Even if the two positive swabs ended up in different groups, you'd still be using only 22 tests — the first round of 12, and going back for ten individual samples. The researchers from Nebraska conducted a study on this and presented the results to the US Food and Drug Administration, the organization responded that they... wouldn't object to it. Basically tacit permission for this approach to move ahead.

Other researchers have proposed ways to get real fancy with the math using computer algorithms, basically optimizing the number of tests that are carried out and narrowing down which samples in a pool are positive. Those proposals need to pass peer review, but pooled testing isn't a new strategy — it's been in use since at least the 1940s. If it's used, this could help us get more bang for our buck where testing resources are limited.

But these tests still won't tell us who's contagious — and that's something we really need to figure out to make the best decisions about who needs to stay home. Still, we're learning more and more about what this disease looks like, even in people who aren't aware they're sick. And hopefully, we'll be able to use that knowledge to beat it.

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