
Proposal for a way to reduce coronavirus infections by optimizing whom to test - mariushn
https://www.linkedin.com/pulse/proposal-way-reduce-coronavirus-infections-optimizing-andreiana
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joe_the_user
The idea that one should limit testing seems extremely misguided.

I would note: South Korea and Italy had equivalent infection figures today.
South Korea's mortality rate has held steady at .6% while Italy's has been
around 4% - quite a bit more death. Basically, strong evidence South Korea is
good model for controlling Covid. [1]

Korea has had a policy of aggressive testing, aggressive tracking infections
and publishing infectees previous locations online (but not names).

There's literally drive-through testing. Anyone who wants to get tested can be
tested. [2]

[1] [https://covid19info.live/](https://covid19info.live/)

[2] [https://www.cbsnews.com/news/coronavirus-south-korea-
drive-t...](https://www.cbsnews.com/news/coronavirus-south-korea-drive-thru-
test-covid-19/)

Edit: Article from the Atlantic: "Exclusive: The Strongest Evidence Yet That
America Is Botching Coronavirus Testing" [3]

[3] [https://www.theatlantic.com/health/archive/2020/03/how-
many-...](https://www.theatlantic.com/health/archive/2020/03/how-many-
americans-have-been-tested-coronavirus/607597/)

~~~
koheripbal
I spoke to someone working in an ER in New York City. People are walking in,
no symptoms, no travel history, no contact with any known cases - demanding to
be tested for coronavirus. They'll say ridiculous things like "my neighbor
(who they've had no contact with) went to Thailand last month. I want to be
tested.". People are panicking.

If tests were infinite, then fine - but as long as we have a finite number of
test kits, there have to be limits.

...but I think we fundamentally agree - we need MANY more test kits. ...and it
would be great to have so many that we could operate at-home or drive-thru
testing. I think we'll get there.

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ganonm
I propose a less effective, but easier to implement, way to optimise who to
test. It relies upon a simple result from network/graph theory that I will
outline here.

Assume, if you will, that typical social networks contain a small number of
people who are highly connected (hubs) and a large number of people who are
much less connected (spokes). The hubs could be e.g. your GP/physician, your
teacher, or even just your popular friend. It would not be surprising if these
people have a much high transmission rate for a virus than people who have a
much smaller social circle - all other things being equal, and also crucially,
they often connect mutliple sub-networks (GP is a good example here).

We would of course like to ensure that we test (perhaps regularly) the people
who are at the center of these networks - the hubs. How do we find out who
these people are? It turns out that you can do this probabilistically. First,
I pick someone at random from the population. I then instruct them to pick a
contact/friend at random. The person they pick is statistically much more
likely to be a 'hub' than a 'spoke', even though we have no explicit knowledge
of the network and carried out this process randomly. A good way to visualise
this is to imagine a toy network of say one person in the middle, connected to
everyone else, and 10 other people, all connected to the person in the middle
but nobody else. You can see that in 10/11 cases, a 'spoke' is selected who
then goes on to select the 'hub' (what we want) whereas in only 1/11 cases the
hub is initially chosen, who then chooses one of the other 10 contacts at
random.

A practical implementation of this could be to choose N people at random and
send them a letter or text message instructing them to pick e.g. the (modulo)
5th person from their contacts list whose name begins with R. They would then
contact this person and inform them that they should present themselves at a
doctor and be tested should they develop any symptoms. There are obvious
optimisations to be made here in terms of name distributions and other
subtleties of course, and certainly providing a list of fallback randomiser
instructions, if they can't find someone fitting that criteria.

Bottom line is, even if many people don't comply, you can increase the
probability that you end up prioritising testing of people who are very
connected, and thus likely to spread disease, which can be invaluable when
your testing capacity is constrained.

~~~
joe_the_user
_A practical implementation of this could be to choose N people at random and
send them a letter or text message instructing them to pick e.g. the (modulo)
5th person from their contacts list whose name begins with R._

I'm sorry but in modern America, you can count on the average person screaming
bloody murder when confronted with a scheme like that. No one likes to be part
of someone else's mathematical model but a random electrician or hairdresser
is toss that away or maybe put out an angry tweet that will get more leverage
than this idea.

------
Leary
2 problems:

1\. The bottleneck in testing capacity in the US will likely be labor.

2\. Testing asymptomatic people is probably not very effective because they
are unlikely to have high viral loads.

~~~
joe_the_user
If the US cannot mobilize sufficient labor to provide testing, this is a
heinous failure of American leadership. And indeed, maybe the US cannot do
this but if a country with a huge state and military sector cannot effectively
"draft" people to engage in the fairly simple processes that would be involved
in just poking a needles or whatever into people, our inability to survive
whatever the next crisis is seems pretty guaranteed.

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martingoodson
I've suggested this exact idea to our health minister a week ago. I think it's
worth investigating. Something similar may be responsible for the
effectiveness of the Chinese response to coronavirus.

~~~
mariushn
[https://menafn.com/1099795540/China-suppressed-
Covid-19-with...](https://menafn.com/1099795540/China-suppressed-
Covid-19-with-AI-and-big-data)

------
s1mon
This is a thought experiment at best. If we ignore the privacy concerns, there
is the basic practical issue that location tracking is often wildly bad and
would lead to tons of false positive and negative selection of people to test.
Over the years I've used a variety of Garmin watches and iPhones to track runs
and walks. In areas with tall buildings or steep hills and trees all of these
systems will jump around and track me as if I were superman bounding
over/through buildings and city blocks from one second to the next.

~~~
mariushn
There are ways to improve that, eg [https://eng.uber.com/rethinking-
gps/](https://eng.uber.com/rethinking-gps/)

It could also give a probability for each case.

I agree it's hard, but maybe there are some cases where it will be effective.
Look at China's current infection rates vs. Italy. Desperate times require
some not-perfect measures. [https://menafn.com/1099795540/China-suppressed-
Covid-19-with...](https://menafn.com/1099795540/China-suppressed-
Covid-19-with-AI-and-big-data)

------
deepnotderp
Can we use homomorphic encryption to deal with the privacy concerns?

