Member of the LessWrong 2.0 team. I’ve been a member of the rationalist/EA communities since 2012. I have particular rationality interests in planning and emotions.
Nothing fancy. In the Bay Area it’s lots of people’s choice:
Rail (BART) usually won’t take you the last mile or two.
Car ownership is expensive (just having somewhere to park is either expensive or your car is likely to get broken into), plus many people never learned to drive, and parking when you go places is a pain.
The buses are awful.
Uber/Lyft aren’t that expensive in this area, or weren’t when pooling with other random people.
People are too lazy to cycle. :P (also bikes getting stolen all the time)
Thanks for this detailed comment. I do think the conclusions of the OP apply for now and one should act on them only so long as a vaccine-evading variant hasn’t become prominent enough to affect overall vaccine protection, and one should be on the lookout for it happening. (I may soon create a mailing list for people to get updates.)After a few hours of hunting, I ended up finding that GISAID seems to be the central place for getting data on variant data. I couldn’t get access since I don’t have an institutional account, however outbreak.info both has an open-access API and pretty good dashboards for tracking variants.I’ll have more of a look at them today.I think now is a bit more like a [potentially brief] Spring and people ought to enjoy the weather before things get frosty again. Though I might update upon looking at the data.
2021/4/24Added some paragraphs at the beginning saying that after looking into variants, my confidence in the conclusions of the post has decreased. 2021/4/22
I removed a short section discussing different false-positive rates among different levels of severity that I now think was confused, following the exchange in this thread.
I added a subsection in the Objections section discussing how the vaccine and control groups in the big Israeli study might be different, and how this should widen confidence intervals.
I thought about this for a while, and I think the entailment you point out is correct and we can’t be sure the numbers turn out as in my example.But also, I think I got myself confused when writing the originally cited passage. I was thinking about how there will be a smaller absolute number of false-positive deaths than the absolute number of false-positive symptomatic cases, because there are fewer death generally. That doesn’t require the false-positive rates to be different to be true.Also thinking about it, the mechanisms by which the false-positive rate would be lower on severe outcomes that I’d been thinking of don’t obviously hold. It’s probably more like if someone had a false-positive test and then had pneumonia symptoms, it’d be mistaken for Covid, and the rate of that happening is only dependent on the regular Covid test false-positive rate.
The quick examination didn’t get into this in the final numbers, but I feel confident that time of day (day vs night) is a big deal. Deaths during the nighttime were roughly the same as daytime deaths, but I’d assume most of the driving happens during the day, and disproportionately deaths are at night, both for visibility or sleepiness reasons.I would advise people against driving through the middle of the night. Even if you don’t feel tired, it’s not good to go against your circadian rhythms.
A perfectly safe driver, for instance, could arguably prevent each of these examples.
A perfectly safe driver, hopefully could. My motivation for wanting to estimate micrmorts was trying to estimate the conversion between microCovids and micromorts for people in the Rationality community. Hence, I’m most interested in the level of safety Rationalists typically have (e.g. seatbelts, not drunk driving) vs population average, so this is pretty good.If I could, I’d get every Rationalist driver to drive vigilantly (“defensively”), take a car-control/defensive-driving course (e.g. this one), keep their car well-maintained (e.g. tires inflated adequately, inspected at least once a year). But most people’s miles are in Uber/Lyft, which is maybe pretty good since those drivers are mostly (a) very practiced, (b) forced to service their cars more reguarly.
Additionally, it’s likely an oversimplification to remove all of a single driver’s share of distracted and drowsy driving crashes, as there’s likely some percentage of those that are unavoidable.
I wish I could say I never drove when tired.
I think we need to track data about these variants and their prevalence.
UPDATEI added a subsection in the Objections section discussing how the vaccine and control groups in the big Israeli study might be different, and how this should widen confidence intervals.
John and I chatted about this for a bit. We agreed that this is technically true but only of practical significance if you expect to get very large number of microCovids anyway. If you’re someone who can control your exposure, it might not be worth the price of information to find out whether your vaccine worked 100%.Neat analogy: you’re playing 100-chamber Russian roulette while wearing head armor that is either impervious to bullets or not. If you’re definitely going to pull the trigger 70 times, then you might as well pull more now. You’ll either die or find out you’re impervious either way. If you have a choice of how many pulls, you might still want to keep it to a minimum, say <10, and never be sure whether your armor works or not.
Nope, that seems roughly right. It is I who failed to propagate. Was a cached argument from before I’d looked at the data.I’ll update the post shortly with this. Thanks for pointing it out.
I think if I were to title this post, it’d be something like “It’s not enough to model internal distortionary forces, you’ve got to model external ones too.” (The current title sounds cool but sans explanation, I don’t see how it matches the content.)And I’d frame the argument as:
When it comes to believing true things about the world, there are distortionary forces both without and within. External people want you to believe things for the sake of their agenda and will optimize aggressively against you for their own interests. At the same time, you too are a political animal and your own mind will optimize against you (and others) for the sake of your own near-term political expediency (cf. Elephant in the Brain and arguments for the primacy of self-deception). To reach truth, you have to model and account for each distortionary environment. Not just one. That means tracking both your own motivated cognition and others’ motivated cognition too.A person who only models their own mind (the naive, inwards-focused bias-correcting Rationalist) will allow others to manipulate their map. A person who only maps the external adversarial environments allows their own mind to manipulate them (especially if they can justify things with reference to external enemies, cf. playbook of oppressive regimes). You must account and attend to both.
Oh yeah, I should have mentioned that mRNA vaccines being a novel type should be factored in. Will edit.
I don’t think it undermines it. What matters is the relative frequency of true cases  vs false positives.With less severe disease (e.g. symptomatic), we might have a frequency of 1% true cases in the population, plus 0.1% false-positive rate. The true cases greatly outnumber the false-positives.
In contrast, vaccinated death from Covid might be only 0.001% in the population, while false-positive deaths are 0.01%. Here the false-positives dominate.
So even though the absolute false-positive rate is lower in more severe cases (because it’s harder to misattribute deaths than get wrong test results), it still dominates the effectiveness results more because it’s larger than the rate of actual occurrences of the event. I say “true cases” deliberately instead of true-positives, because I mean to say the objective underlying frequency of the event, not true-positive detection rate.
As defined by the hospitalizing institution per the Israeli MOH guidelines, consistent with the NIH criteria for severe illness or critical illness:
Individuals who have SpO2 <94% on room air at sea level, a ratio of arterial partial pressure of oxygen to fraction of inspired oxygen (PaO2/FiO2) <300 mm Hg, respiratory frequency >30 breaths/min, or lung infiltrates >50%. Critical Illness: Individuals who have respiratory failure, septic shock, and/or multiple organ dysfunction.
APPENDICES & FOOTNOTES
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I reckon it’s fine, especially if you provide the source.