Hey guys! Welcome to the osmosis daily report on the coronavirus pandemic. I'm Dr. Rishi Desai.
I'm the chief medical officer at Osmosis,
also a pediatric infectious disease doctor, and I used to work at the CDC in the division of viral diseases doing viral disease outbreaks.
So, today I wanted to talk a little bit about the topic of testing and specifically
RT-PCR and an interesting idea called block testing. Before I get to that let me just jump into the data.
Here we are, we've got a total of 1.3 million cases confirmed worldwide and
74,000 deaths. In the U.S. we have about 30 or actually
360,000 of those cases, leading by far the world right now. This is a pretty cool website. It's the COVID tracking project
website and they show historical data for the U.S. state-by-state, day-by-day in terms of how much more testing is being done.
You can see we're at 1.9 million right now in total.
And if you just kind of go down here and look at roughly a week ago,
so one Monday ago, we were sitting at 940,000.
So really have gained about a million extra tests in the last seven days.
Which is phenomenal because up until that point we've been
struggling to see the number of tests go up and now it's happened with the private sector kicking in.
This isn't happening equally across the country,
So some some cities are seeing more testing, others are seeing less.
Some labs are actually able to do more than others and there's some capacity sharing where they're saying, "Hey, send us your specimens,
we'll do the testing here and we'll send them back to you".
So when you see that sort of capacity sharing, what that tells you is that this is unevenly distributed.
The good news is that this is hopefully gonna ramp up in the days to come.
Now the number we're at is roughly 170,
sorry, one test for 170 individuals in the nation, which is good and it's actually kind of the level
we saw South Korea had, but I'll keep
mentioning the fact that South Korea had far fewer cases.
So, given that, we still need to ramp up the testing much much more and see it evenly done across the countries. In
particular, in areas where we're getting much testing where the resources are pretty poor.
Now the association of Public Health laboratories has put out guidelines in terms of who should get testing. And up until now,
because testing has been so limited, it's been you know, let's just test
the sickest patients and even then it was often hard to come by. As I said,
it's gonna get easier I think in the days and weeks ahead because we're starting to see more testing being done.
So, let's take a look at the other priority patients that the
APHL recommends. So they have priority 1 for hospitalized patients and healthcare workers.
Obviously that makes sense. Priority 2 for high-risk individuals like first responders as well as those that are elderly and have other health conditions.
Priority 3 is an area where I want to kind of flag one group in particular - health care workers and first responders.
But you notice it doesn't stay with symptoms.
So here what they're saying is that it might make sense to be testing those individuals to make sure that
they're not getting sick or that they're not pre-symptomatic or asymptomatic but carrying the disease.
So that got me thinking about that group. Where,
presumably you should be seeing more negatives. You wouldn't expect as many positives.
Maybe you see a few and you want to catch them early. And so what some countries are doing is quite interesting.
This is a New York Times article on Germany and I highlighted it a little paragraph that really caught my eye.
This is about testing that's being done there.
They said medical staff at particular risk of contracting and spreading the virus are
regularly tested and to streamline the procedure they've done something called block testing where they use swabs of ten employees and
test
In follow-up only if one of them gets positive. So let me explain what block testing is.
I think this is a really fascinating idea that we could employ to really rapidly scale-up testing without much extra cost.
There's this research article that puts forward the idea -
this is a German article, and what they basically are showing is that you get swabs but instead of testing each swab
individually, you take all the swabs and test them together and if there's a single positive then you go back and then you test all
the individual swabs separately.
So, when they did this what they found was that actually the pool testing had no influence on the detection limit. In other words,
what they're doing is because they're taking multiple swabs and they're not changing the volume of liquid in any way,
there's actually no change in sensitivity. Which is amazing!
So you're basically running fewer tests, but you're not changing the sensitivity. You're still getting that really
same ability to detect the virus from any of them, but you're doing it quicker and using less resources.
So, you know I like video and so they have a video explaining this which I thought was really really awesome.
In short, imagine you have a hundred healthcare workers and you want to check them every week to make sure you don't find anyone
that's positive with COVID. Here there's one red dot. One healthcare worker that has COVID.
Maybe they have no symptoms, or such mild symptoms
they don't even notice them, but they're coming to work and you want to catch them.
Well one way to do it is to simply just run a hundred tests.
That would be the traditional way to to screen people. You just one test per person.
So the total test in that situation would be a hundred. What they're proposing here is something quite different.
They're calling it batch testing or block testing. But watch what they do.
So basically they're running ten samples at a time.
They've only done five tests so far, but they've done fifty people. They go all the way through and then in this eighth batch
they've got that red case so that one will be positive.
So that entire batch then they go back and they do all those individuals separately.
So now the number of total tests is rising, but again
it's only gonna get to 20 and they're gonna be able to identify and hone in on that one person that had a positive test
pretty effectively.
So you went from doing a hundred tests to doing only twenty tests. Which is pretty profound, right? Twenty percent of the total amount of testing. And then they brought up a good point.
They said what if you actually had smaller batches within that ten. You could actually cut down testing further, right?
It's almost like a logic riddle.
So in this case they said, well
what if we had ten people divided into two batches of
five. The first batch might be negative.
And in this case that had two positives. But then in the second batch you'd be able to do five tests and say hey
let's pick up all five individuals and find the two individuals that have a positive.
In essence you went down, instead of going from 100 to 20, you actually went down using this technique from 100 to
17. You can come up with different clever ways of doing it.
Maybe you you go 3, 3, and 4 or however you want to do it.
Bottom line is you don't need to test everybody to get the same benefit. And the final point that they make, which I think is
profound, was that really when you study this you could say, "Hey, what's the largest batch
you can work up to, to really scale this out where you're still getting reliable results?".
So that's really the question but the bottom line is I think
everybody should be looking at this really hard. As we scale out testing, and as we start testing more people, where your
pretest probability or your your assumption is that you're gonna get more negatives goes up,
this approach really makes a lot of sense to cut down on the resources you need but still find all those
individuals. And maybe you could test them weekly and doing this you could actually pull that off using fewer resources.
So I hope you enjoyed that. I thought that was pretty powerful.
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Remember do your part to raise the line and flatten the curve. We're all in this together. Thanks a lot.