Predict the FINAL NUMBER of confirmed Coronavirus cases/deaths in the U.S. (Predictions ONLY)

That means we have to hope there are really millions infected. If the # is correct, this thing is batting .500 plus. I'm assuming recovered includes non symptomatics who test positive then after a while test negative.
 
But totals cases are not resolved. I think the death percentage is way higher than fucking 1%. It's clocking in over 50% with *resolved cases.
The general thinking is that of those who get sick enough to get tested(far less than half of infections), about 15% are hospitalized, of those maybe half end up in the ICU, of those maybe half die.

That's why the estimate is somewhere around 1%.
 

Valuist

EOG Dedicated
But totals cases are not resolved. I think the death percentage is way higher than fucking 1%. It's clocking in over 50% with *resolved cases.
Nobody reports "resolved cases". If you are sick with it, then recover, nobody is calling authorities to proclaim Joe Blow has now recovered. Case numbers is the denominator. Ignore the "resolved cases".
 
A "resolved (or 'recovered') case" requires 2 negative tests in a row over a 48 hour period.

I guarantee that's only being done for patients who are hospitalized with severe symptoms and wind up getting follow up tests as part of a discharge protocol after they've improved. . they aren't wasting those tests on your average Joe Blow with mild symptoms, thus Joe Blow will never get counted as "resolved."
 

John Kelly

Born Gambler
Staff member
I have a feeling its gonna be a long, long contest. For contrast, I'll take the other side with JK, Abundy and jb777.

I'm sending my résumé to the CDC and WHO.

Only one problem: I don't know the difference between a microbe and an enzyme.
 
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John Kelly

Born Gambler
Staff member
Let us start by denoting with S(t), I(t), R(t), D(t), the number of susceptible, infected, recovered and dead persons respectively at time t in the population of size N. For our analysis, we assume that the total number of the population remains constant. Based on the demographic data for the province of Hubei N = 59m. Thus, the discrete SIRD model reads:
(1)
(2)
(3)
(4)

The above system is defined in discrete time points t = 1, 2, …, with the corresponding initial condition at the very start of the epidemic: S(0) = N − 1, I(0) = 1, R(0) = D(0) = 0. Here, β and γ denote the “effective/apparent” per day recovery and fatality rates. Note that these parameters do not correspond to the actual per day recovery and mortality rates as the new cases of recovered and deaths come from infected cases several days back in time. However, one can attempt to provide some coarse estimations of the “effective/apparent” values of these epidemiological parameters based on the reported confirmed cases using an assumption and approach described in the next section.
 

John Kelly

Born Gambler
Staff member
Not a good time to be a modeler.

#Exposed

If CDC modelers were forced to make a living in Las Vegas, they'd be working for the house, not living "on the house."
 
Scoring formula in Bold:

What exactly is the scoring criteria anyways? Are deaths weighted heavier (as they should be) than cases?
I'll be glad to do the grading, however I think I need to clarify/modify the formula given by EJD.

Restatement 1, add paren after deaths: Grading formula is (difference between prediction and actual number of cases) + (difference between prediction and actual number of deaths) x 25

First, his example, the score is 1000000 -1150000 + (10000 -12000) x 25 = -200,000.

Restatement 2, use absolute value of the differences so score is always non-negative: Grading formula thus is abs(difference between prediction and actual number of cases) + abs(difference between prediction and actual number of deaths) x 25

Deadline is Thursday 11:59PM CT, thus 9:59PM PT tonight, 12:59AM ET, Friday morning.

Will look for EJD's concurrence.
 
A lead change (6 leaders), VD and EJD tied for first, the tie will last about 3 days (till cases >500,000), EJD will then lead for about 6 more days:

1586411487555.png
 
Not a good time to be a modeler.

#Exposed

If CDC modelers were forced to make a living in Las Vegas, they'd be working for the house, not living "on the house."

They are like DiCaprio back in the day, they change their models daily.

If a particular day's data is different, they chuck their models and come up with new one.

They are good at finding lagging indicators not leading ones
 

Ray Luca

EOG Dedicated
The guys in the herd immunity corner do not understand this virus is transmitted too easily therefore you would need 60 percent of people infected and then rendered immune to wipe it out
 
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