
Finding SARS-CoV-2 carriers by optimizing pooled testing at low prevalence [pdf] - FuckButtons
https://www.medrxiv.org/content/10.1101/2020.05.02.20087924v1.full.pdf
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zmmmmm
People seem to be missing the point of this article. Pooled testing is
accepted and routine. The point of the article is that by constructing pools
and subpools in a particular way you can dramatically speed up the process by
exercising in parallel / up front all the possible testing paths that would
normally have to occur in series so that the individual(s) who are positive
are identified in only one round of testing - giving a crucial advantage in a
time sensitive situation such as contact tracing for infectious diseases.

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rgbrenner
Yes, and it's already been done for covid. In may, China wanted to test all
11m people in Wuhan, so they used pooled testing:

[https://www.livescience.com/pooled-sampling-covid19-in-
wuhan...](https://www.livescience.com/pooled-sampling-covid19-in-wuhan-and-us-
cities.html)

~~~
FuckButtons
The algorithm presented in this paper is a significant improvement over what
was done in wuhan. In a low infection population it reduces the cost of
testing an individual to around $0.75 and can find infected individuals in a
single step, without having to do subsequent assays to narrow down which
samples tested positive.

~~~
bhickey
Array testing is an improvement over Dorfman, but this has been widely known
for decades. Blood banks regularly use high dimensional arrays for testing.
Here they test the hypercube planes in serial instead of parallel, but this
increases latency and decreases sensitivity.

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bhickey
I think to authors are overly optimistic in our ability detecting highly
dilute samples. Pooling studies in Dengue Fever using RT-PCR found sensitivity
fell faster than could be explained by dilution effects alone. At 100:1 or
20:1 pooling the false negative rate will be unacceptable.

Edit: false positive -> false negative

~~~
virusduck
False negative rate maybe?

In general, titers of the virus in NP swabs should be high enough to withstand
10, maybe 20-plex pooling. However, as you allude to, there are plenty of
other effects that can influence PCR. If there is one sample, for example,
that contains a PCR inhibitor, like heme, it may then inhibit all the samples
it is pooled with.

Additionally, swabs are not just swabs of virus, they also pull of highly
variant amounts of bacteria and human material. These things may also affect
the efficiency of PCR.

~~~
bhickey
> False negative rate maybe?

Yes, thanks, fixed.

Check out Table 1 in this paper. It isn't very encouraging.
[https://onlinelibrary.wiley.com/doi/full/10.1002/jmv.25971](https://onlinelibrary.wiley.com/doi/full/10.1002/jmv.25971)

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travisporter
Aha! Someone must have read my comment on HN.
[https://news.ycombinator.com/item?id=22616288](https://news.ycombinator.com/item?id=22616288).
Where's my citation lol

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FuckButtons
I was listening to the bbc’s science in action podcast[0] and came across an
interview with the mathematician whose group had developed this.

By mapping individuals onto a hypercube they were able to reduce the number of
tests needed to find unique positive individuals by a very large percentage
relative to non pooled testing as long as the positive test rate was low in
the population.

[0]
[https://www.bbc.co.uk/sounds/play/w3cszh0k](https://www.bbc.co.uk/sounds/play/w3cszh0k)

~~~
magnio
A link for those who prefer reading:
[https://www.nature.com/articles/d41586-020-02053-6](https://www.nature.com/articles/d41586-020-02053-6)

It seems like this method can be generalized to a detection problem. Anyone
knows other applications of this technique?

~~~
lp251
[https://en.wikipedia.org/wiki/Group_testing#Example_applicat...](https://en.wikipedia.org/wiki/Group_testing#Example_applications)

~~~
pmiller2
Isn't this just an extension of one of those dumb brainteasers people
sometimes ask in interview questions? (You have N rats and K vials, P of which
contain poison. Can you determine which vials contain poison?)

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MatthiasWandel
Like so many clever puzzle answers, this doesn't take into account the effect
of measurement error. The tests apparently have a false negative rate of 20%
as it is. Now start mixing samples together, causing more dilution of the
positive samples, and the false negative rate is bound to go up further. Now
you have to do studies to figure out what the false negative rate is going to
be, and put that into your model as well. This could get impractical fast.

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jupp0r
I’m not a virologist, but from my understanding the false negative rate is
caused when collecting swab samples and not related to the concentration
during the PCR. There are also thresholds in the process (mainly the number of
reaction cycles) that can be tuned to account for lower concentrations.

~~~
virusduck
That is correct.

