Comment by yourapostasy | Hacker News Reader

Comment by yourapostasy | Hacker News Reader

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Appreciate the input.

Ethical issues: I'm thinking in terms of underserved communities where tests are simply unavailable. A 60% false negative rate test is better than no information whatsoever. After all, it was good enough for China to use (along with authoritarian powers to quarantine) to help get a handle on containment, or what am I missing?

Considering the abysmal US track record serving the healthcare needs of lower socioeconomic strata, I'm not sanguine on them receiving the tests we need to even get an approximate handle on the public health situation.

So if we narrow the scope to just testing for Covid-19, are you saying it still takes several years to get to the point of just administering and evaluating the test, right?

If so, then that means testing is staffing constrained, and you're implying it is impossible in a situation like we face now to dramatically expand the testing scale/volume, and the entire US Federal plan to test orders of magnitude more is complete bullshit.

So is this one of the few areas of human endeavor that is absolutely non-automatable, or can we break down what is/is not within the realm of automation, and possibly leverage the few staff we have relative to the current need?

Or can we relax quality constraints in an emergency like this to favor false positives over false negatives to focus on flattening R0 (although everything I've read so far seems to indicate false negatives are the bigger concern)?

So please give some pointers, where do you see specific, concrete problems for starters that others with domain expertise can look into to evaluate?

A 60% false negative rate test is better than no information whatsoever.

No! It's decidedly not better! This isn't web-scraping where any little bit of information you extract is good, even with a low signal-to-noise ratio. These are human beings. Being wrong here has serious consequences, to the point that you need to weigh the usefulness of the test against the risk of harm of misdiagnosis. You can't just go around diagnosing people willy-nilly if you're not sure about the results!

A false negative means someone will go out with a false sense of security, potentially interacting with vulnerable community members thinking they'll be fine. They may develop further complications due to writing off their symptoms as the flu, and not seek out medical intervention if the situation goes South. A false positive means someone is going into quarantine for two weeks at a major economic and housing consequences (particularly if you want to help poor communities). False positives and false negatives mean more lives will be lost. The stakes are higher, and so too is the need for ethical rigor.

So if we narrow the scope to just testing for Covid-19, are you saying it still takes several years to get to the point of just administering and evaluating the test, right?

I'm not saying the test will take several years to develop, I'm saying it would take you, a self-described layperson, several years to gain the technical skill and know-how to know how to correctly research, design and validate the test.

Specifically, labs are carefully controlled environments. Just getting into the grunt work mechanics of the technique, at bare minimum you need to learn aseptic technique, pipetting, sterilization, reagent prep, handling hazardous chemicals, biohazardous waste disposal, and establishing appropriate environmental controls for your lab. Starting from nothing, those will take at least a year of full-time experience to develop for any semblance of competence. Otherwise you'll be a bull in a china shop; your results will be too tainted by bad technique and inadequate environmental controls to get anywhere.

So is this one of the few areas of human endeavor that is absolutely non-automatable, or can we break down what is/is not within the realm of automation, and possibly leverage the few staff we have relative to the current need?

It's perfectly automatable, but that doesn't mean it's trivial. For one, someone needs to... actually automate it. Someone else needs to implement, maintain and troubleshoot the robotic lab equipment doing the automation. Still require highly specialized skills to do so.

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