Comment by kdbscott on Will COVID-19 survivors suffer lasting disability at a high rate? · 2020-03-22T01:19:44.486Z · score: 5 (3 votes) · LW · GW

Here's a paper (posted 25 Feb) outlining neurological symptoms in 214 Chinese hospital patients:

  • 126 non-severe patients, 38 of which had 'neurologic symptoms'
    • 3 with impaired consciousness
    • 1 had an ischemic stroke
  • 88 severe patients, 40 of which had neurologic symptoms
    • 13 had impaired consciousness
    • 4 had an ischemic stroke, 1 cerebral hemorrhage

I don't know how much this differs from base rates - like if I have hypertension and need to go to the hospital because I broke my wrist, how likely is it that my brain also goes haywire? Or if I get a fever?

Comment by kdbscott on March Coronavirus Open Thread · 2020-03-15T07:27:51.956Z · score: 12 (5 votes) · LW · GW

Did you end up finding one besides the MIDAS network, or develop your own? I'm assembling a parameter doc for inputs to a rough model that accounts for ventilator & hospital bed capacity, since it seems like we're lacking that.

  • I encourage folks to add parameters w/ citations to the doc, I'll be active on it for the next few days.
  • If anyone knows of models that incorporate actual healthcare capacity, please share!
Comment by kdbscott on March Coronavirus Open Thread · 2020-03-14T22:29:16.393Z · score: 8 (3 votes) · LW · GW

I've been a bit confused about doubling rate. First, I noticed that many numbers (e.g. Wikipedia) are calculating how long it took to double, instead of projecting forward using e.g. yesterday's increase. Early on this led to misleading numbers, but recently the US has been steady around 2-3 days using both methods.

However, I'm guessing that raw doubling rates depend a lot on testing, and that the US should expect to have a faster-than-actual doubling rate until our testing catches up. So I lean towards Trevor's number of 5 days.

Comment by kdbscott on 2014 Survey of Effective Altruists · 2014-05-01T23:02:57.928Z · score: 3 (3 votes) · LW · GW

Good point about LW affiliation - in addition I would add that results are highly dependent on how the survey is distributed. This makes large predictions difficult, but more specific predictions (like >80% of LW affiliations will identify as atheist/agnostic) might be the way to go.

I'm still getting familiar with this community, but I suppose it's a fun exercise so I've added some thoughts to the excel sheet.