@deepthought saidI suppose you wouldn't be pointing to this if you believe that they might truly just offset in the ranking?
@joe-shmo
One thing you haven't included is the rather double edged GDP per capita. On the one hand a high GDP implies the presence of resources to fight the disease, treat the ill and so forth; but on the other a country with a low GDP per capita might have relatively little internal movement, so that the virus spreads slowly due to absence of mobile hosts.
6 edits
@joe-shmo saidRevision 2: Data as of 4/8
Looking to have a rational discussion on devising a simple/effective ranking for how well certain countries are doing. I keep hearing certain people shouting how terrible the USA is responding to this.
Here is what I propose as a simple scoring system. Improvements are welcome.
all data comes from
https://www.worldometers.info
I first sorted the data by Total D ...[text shortened]... eople down with mere opinion.
So as I said, I welcome thoughtful critiques, improvements, ect...
Filters:
Population > 10 Million
Test/MIll > 2600
Revision to Score System I added a correction factor For "Date of Exponential Onset." My goal is to compare the countries on similar timescales by shifting them toward the median "Date of Exponential Onset" for the group. Early to Mid Development the "Cumulative Deaths" looks like an exponential function. So we might let the median country have a curve of the form:
Y = e^(m*t)
A country shifted away from the median curve ( either earlier or later in time) will have the form:
y = e^(m*( x -x_o ) )
I wish to scale "y" in such a ways as to project where it would be if it had been growing since the median date of the curves.
k*y = Y ==> k = Y/y
k = e^(mx) / e^( m( x-x_o) )
Letting the median "x" value be zero implies:
k = e^(m*0) /(e^m(-x_o) ) = e^(m*x_o)
The median date for Exponential Onset ( Date the log graph of cases becomes Linear) was 3/5. Countries with later start dates will have positive x_o ( acting to increase the score), and before will have negative x_o values(acting to decrease score)
I also used the log plots to determine for a sample of counties the slope of the Cumulative Deaths. I performed a weighted average of those values by population. I determined "m" = 0.3. Values ranged from 0.5 to 0.2, they were predominantly clustered around 0.3.
The New Scoring is as Follows:
Score = (Tot Deaths/Mill)*(1/Density)*(1/Med Age)*e^(0.3*x_o)
The latest ranking is as follows:
Country.....Tot D/10^6.....Test /10^6.....Pop......…….Den …….Med Age.....Date of Exp Onset.....Days from Median Day.....Time Corr. Factor.....Score
South Korea...…...4...…......….9,310........51,269,185.........527.........44.........…...2/26/2020............…………...……...-8.........…...…..........0.07730474...…..................1
Germany.....29.....15,730.....83,783,942.....240.....46.....3/1/2020.....-4.....0.2780373.....73
Azerbaijan.....0.9.....5,658.....10,139,177.....123.....32.....3/10/2020.....5.....4.953032424.....113
Czech Republic.....10.....9,977.....10,708,981.....139.....43.....3/5/2020.....0.....1.....167
United Kingdom.....105.....4,155.....67,886,011.....281.....40.....2/29/2020.....-5.....0.201896518.....189
Poland.....5.....2,843.....37,846,611.....124.....42.....3/9/2020.....4.....3.596639726.....345
Chile.....3......3,576.....19,116,201.....26.....35.....3/6/2020.....1.....1.377127764.....454
Russia.....0.5.....6,885.....145,934,462......9.....40.....3/9/2020…..4.....3.596639726.....500
Australia.....2.....12,946.....25,499,884…..3.....38.....3/1/2020.....-4.....0.2780373.....488
Netherlands.....140.....5,926.....17,134,872.....508.....43.....3/5/2020.....0.....1…..641
France.....167.....3,436.....65,273,511.....119.....42.....2/29/2020.....-5.....0.201896518.....675
Spain.....326.....7,593…..46,754,778.....94......45......2/27/2020.....-7.....0.106458504.....820
United States.....49.....6,971......331,002,651.....36.....38.....3/2/2020.....-3.....0.382892886.....1371
Greece.....8.....3,227.....10,423,054.....81.....46.....3/12/2020…...7.....9.393331287…...2017
Canada.....13.....9,812.....37,742,154.....4.....41.....2/29/2020.....-5......0.201896518......1600
Belgium.....218.....7,269.....11,589,623.....383.....42......3/6/2020.....1.....1.377127764......1866
Portugal.....40.....13,766.....10,196,709.....111.....46.....3/11/2020.....6.....6.820958469......5343
Sweden.....79.....5,416......10,099,265.....25......41......3/6/2020......1......1.377127764......10614
Again: Countries Like" Vietnam" and "China" where omitted due to below average testing rates. I suppose its fair to say if they were in the comparison they are ranked 1 & 2 respectively.
Countries Italy, Iran, Kazakhstan, Turkey were omitted because they were at/or father than 10 days out ( at their time of onset) from the median date of exp onset - 3/5
As always any questions, concerns, feedback please feel free to engage!
PS: Please excuse the formatting.