Previous weekly reports: Covid-19 5/7: Fighting Limbo, Covid-19 4/30: Stuck in Limbo
Slowly, a nation partially reopens. Is it too much, too soon? It’s too early to know for sure, because of lags, but so far we’ve only seen extraordinary good news. If you don’t think what we saw this past week was good news, either we disagree about how to read the data quite a lot, or you had what I consider highly realistic expectations.
Remarkably little has happened in the last week. There are weeks when decades happen, and previous weeks have felt like that. This one didn’t. This felt like waiting for things to happen and nothing happening except good numbers. Yes, we got some other news, but did any of it matter or surprise much? I would say that it did not.
Last time I did a bunch of analysis and a bit of editorializing alongside the numbers. This time I’ll keep it brief. This is mostly to get the charts out. I’ll get the other stuff out there in distinct posts if it’s worth saying.
Legends of Runeterra has been getting a generally favorable reception. The game is highly relevant to my interests as someone who plays a lot of collectible card games and is making a collectible card game of my own called Emergents, together with Brian David-Marshall, that will be ready for its first Alpha test soon.
Thus, after the latest round of prompting to check the game out, I have checked the game out. I figured I should report back.
We’ve all seen statistics that most people who die of Covid-19 have at least one comorbidity. They also almost all have the particular comorbidity of age. The biggest risk, by far, is being old. The question that I don’t see being properly asked anywhere (I’d love for this post to be unnecessary because there’s a better one) is: What is your chance of death from Covid-19 if infected, conditional on which if any comorbidities you have? Which ones matter and how much? If you don’t have any, how much better off are you than your age group in general?
Thus, most people are looking at the age chart, without adjusting for their health status, unless they have an obvious big issue, in which case they adjust up. Which leads to an incorrect overall answer. That isn’t obviously a bad thing in terms of resulting behavior in practice, but that doesn’t mean we shouldn’t attempt to figure out the answer.
Last week: Covid-19 4/30: Stuck in Limbo
Recently: Covid-19: New York’s Antibody Tests 2, On “COVID-19 Superspreader Events in 28 Countries: Critical Patterns and Lessons”
Background Assumptions: On R0, Taking Initial Viral Load Seriously, On New York’s Antibody Tests, My Covid-19 Thinking: 4/23 pre-Cuomo Data
Spreadsheet where I do work: Access it here as read only
Deaths By Week in the 5 Big Regions:
|Mar 26-Apr 1
|Mar 19-Mar 25
|Apr 30-May 6
Previously: On New York’s Antibody Tests
New York continues to be the only place even trying to do antibody tests in a way that involves releasing information on the population.
What do we now know? How should we update? What comes next?
As a reminder, the method of data collection seems to be to set up in a randomly selected set of geographically distributed grocery stores, with volunteers who are then told their status afterwards.
Response to (Elizabeth @ LessWrong): Negative Feedback and Simulacra
Requires/Assumes (Compass Rose): Simulacra and Subjectivity
Epistemic Status: Exploring, thinking out loud, taking a break from Covid-19 stuff, etc. Long post is long because I didn’t have the time or insight to make it shorter. Later I hope to write shorter versions.
Simulacrum levels are very important. If you haven’t read the Compass Rose post above, please do so, even if you don’t read the rest of this post. At a minimum, read part 2 of Elizabeth’s post above, which attempts to summarize the central point.
Elizabeth’s post provides good relatively clean examples of a common problem related to simulacrum levels.
The common problem – in fact, the most common problem – is that there is a desirable action X that you wish to take, or an undesirable action Y that you wish to avoid. Unfortunately, taking action X, or avoiding action Y, has undesirable (at least to someone, in some sense) consequence Z.
Previously: Evaluating Predictions in Hindsight
Epistemic Status: Having fun
Evaluating predictions is hard, especially about the future. Let’s do it.
The most frustrating part of predictions is defining them carefully. A lot of Scott’s 2020 predictions seem like they have a high enough probability of a disputed outcome that they’d require clarification before betting on them. A bunch of others say they’re explicitly Scott’s decision. Thus, I’ll try to clarify how I interpret such proposals as part of my evaluation.
I’ll be looking at the predictions as if they were markets, and asking whether I would buy (bet on the thing happening at those odds plus some fee), sell (bet against the thing happening at those odds plus some fee) or hold (not inclined to wager), and about where I’d put my fair. Note that this doesn’t mean I’d bet against Scott because Scott believes the prices are fair. So we’d have to give him good enough odds that he’d be willing to bet.
First up, we have the Coronavirus predictions. You’d pay to know what you really think! Hence, betting markets.