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PCR tests for Covid-19 are pretty accurate. But they're often very slow and they can be hard to get. Results sometimes aren't available in time to be useful. Faster tests can be less accurate. As we try to reopen schools and businesses we need to take a hard look at how we're conducting testing.

Related HCT episodes:
Blood Types and Covid-19: https://youtu.be/dcVl-FIu5AI

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#healthcaretriage #coronavirus #covid
Extensive COVID-19 testing is critical to identifying and isolating cases in order to significantly contain spread. If we want that—and we do—we've got to start thinking about testing differently. That's the topic of this week's Healthcare Triage. 

[Healthcare Triage intro animation & music]

Our current PCR-based method of testing for COVID-19 is pretty accurate, which is good for detecting positive cases. But that's not a huge plus if we're missing a bunch of cases anyway due to low levels of testing. And we are.

Some estimates suggest that infections are around 10 times more prevalent than are being detected and reported. Often times, presumably due to cost, resources, and time, tests are being saved for the sickest. This means we're missing a lot of people with mild or no symptoms who have the full potential to spread the virus further if they don't know to self-isolate and we don't know to do contact tracing. 

Plus, in many cases it can take anywhere from 10 to 15 days to get test results. Given that this is generally longer than a person is actually infectious, it renders testing useless for the purpose of limiting spread, particularly when an individual is asymptomatic. That's the trade-off here: we've got high accuracy, but with tests that are slow, expensive, and running short of necessary supplies. 

As Dr. Ashish Jha wrote recently, when it comes to controlling a pandemic, speed matters much more than test sensitivity. I also wrote about this recently at the New York Times. What matters is the frequency and speed of testing. We could mass-produce tests and run them in large groups, and we wouldn't need a lot of supplies to do it, which means we can not only test a lot of people, we can retest them as often as we'd like. By changing the way we collect and run samples, we can potentially course-correct our current situation; we just have to be willing to accept that the results will not be as accurate as those of the more time- and resource-consuming tests that are in play right now. 

Because yes, employing high levels of less sensitive tests would would likely mean missing positive cases. But I'm still calling it a course corrector, because we'd likely be able to catch more cases than we are with our current abysmal rate of testing and results. We simply can't improve those rates or result times while demanding pinpoint accuracy at the same time.

We've got to weigh our options, and in this case, the better option seems clear. We can either keep detecting around 1 in 10 cases—usually long after they are no longer infectious—or we can detect more infections within the window of time where isolation is key, accepting that we'll have inaccuracies along the way. 

And it's not like we have to go about the business of developing these quicker, cheaper tests from scratch. We've got at least one that has already been FDA-approved. However, there's been significant pushback from those who are concerned about potentially high rates of false negatives. The data we have and the situation we're currently in beg for those people to reconsider their position. 

The stakes are high when we're talking about sending our kids back to school and attempting to avoid catastrophic damage to the economy. We've got to catch up to this virus, and our best option is to speed up testing. As I wrote recently, more is sometimes better than perfect.

Hey, did you enjoy this episode? You might enjoy this previous episode on blood types and COVID-19. We'd also like if you'd like and subscribe down below, and consider going to patreon.com/healthcaretriage, where you can help support the show even as we try to exist in a pandemic. We'd like to especially thank our Research Associate: James Glasgow, Joe Sevits, Josh Gister, Michael Ginn, and, of course, our Surgeon Admiral Sam.