March 24th: Daily Coronavirus Link Updates

post by habryka (habryka4), Ben Pace (Benito) · 2020-03-26T02:22:35.214Z · LW · GW · 6 comments

Contents

  Dashboards
    Dashboard with estimates and predictions of true prevalence
  Economics
    What will the economic effects of quarantine be?
  Medical System
    Flexport CEO explains why scaling PPE is hard
  Other
    Stories of C19 layoffs
  Spread & Prevention
    Review of mask efficacy
    LW Advice Summary
  Work & Donate
    LessWrong C19 Agenda
  Full Database Link
None
6 comments

As part of the LessWrong Coronavirus Link Database, Ben, Elizabeth and I are publishing update posts with all the new links we are adding each day that we ranked a 3 or above in our importance rankings. Here are all the top links that we added yesterday (March 24th), by topic.

You can find the full database here: https://www.lesswrong.com/coronavirus-link-database [? · GW]

Dashboards

Dashboard with estimates and predictions of true prevalence

A dashboard that gives you estimates for current prevalence by country, as well as predictions for the future based on varying amounts of mitigation.

Economics

What will the economic effects of quarantine be? [LW · GW]

LW attempts to predict what the effects of a short or long quarantine will be

Medical System

Flexport CEO explains why scaling PPE is hard

Outlines the difficulties in scaling, including QA and legal issues

Other

Stories of C19 layoffs

Reddit thread of people who lost their jobs due to coronavirus or quarantine

Spread & Prevention

Review of mask efficacy

They're useful but the gains may be overwhelmed by any risk compensation, and they need to be saved for medics

(EV) He left out a swath of studies on mask use in mass gathering

LW Advice Summary [LW · GW]

A summary of the best suggestions from the justified practical advice thread

Work & Donate

LessWrong C19 Agenda [LW · GW]

A list of questions we want answered to inform future decisions, and assembly of answers as they're created

6 comments

Comments sorted by top scores.

comment by cousin_it · 2020-03-26T16:26:25.317Z · LW(p) · GW(p)

Does anyone know why the dashboard says infections will peak at 3% if no mitigation is done?

Replies from: habryka4
comment by habryka (habryka4) · 2020-03-26T17:08:07.862Z · LW(p) · GW(p)

That’s active infections. That number corresponds to something like 70% of the population having been infected at some point.

Replies from: cousin_it
comment by cousin_it · 2020-03-26T18:09:39.790Z · LW(p) · GW(p)

It still looks weird to me. For example, in Switzerland with no mitigation it estimates 1% of people infected now and 3% at the peak on Apr 14, which is 2.5 weeks from now. Since each infection lasts a couple weeks or more, and there have been few deaths and recoveries so far, that means <5% of the population will have been infected by that point. And then it says active infections will start falling. Why?

Replies from: habryka4
comment by habryka (habryka4) · 2020-03-26T19:09:32.650Z · LW(p) · GW(p)

I think the model uses a much shorter time for active infections than 2.5 weeks. Not sure what it is, but I think it's closer to 5 days or something like that, which seems to actually fit the behavior of the disease best, on a broad scale. 

Agree that it looks weird. I've asked the authors of the project to add a cumulative graph, which makes these assumptions a lot clearer.

Replies from: jacobjacob
comment by jacobjacob · 2020-03-26T20:37:24.522Z · LW(p) · GW(p)

We used parameters based on a paper modelling Wuhan, that found that ~2 day infectious period predicted spread the best.

Adding cumulative statistics is in the pipeline; I or one of the devs might get around to it today.

Replies from: cousin_it
comment by cousin_it · 2020-03-27T07:29:11.912Z · LW(p) · GW(p)

Wait, so your graph shows the number of people having their 2-day "infectious period" at any given time, which could be much lower than the number of people infected at a given time? That doesn't seem to be explained on the page.

Anyway, I think the really important number is how many people are having their "required hospitalization period" at any given time (which is longer than 2 days). Maybe you could show that too, since you're already showing the "care capacity" line?