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Some Hard information on #COVID19 as compared to other epidemics in recent history.
==COVID-19==
R0 = 2.2
Global Mortality: 7%
Death Toll = 4,718 (and rising)
== 2009 Swine-flu ==
R0 = 1.5
Global Mortality: 0.04%
Death Toll = 500,000
== 2002 SARS ==
R0 = 3
Global Mortality: 9.6%
Death Toll = 349
== 1920 Spanish Flu ==
R0 = 2
Global Mortality: 2.5%
Death toll = 100 million
For those who don't know R0 is the average number of people who will contract the disease from an infected individual.
As you can see the numbers are very concerning. The only disease that had the same potential for damage as this would have been the SARS epidemic in 2002. Luckily it was contained early on and never spread. The big difference seems to be the 2002 SARS epidemic had very few if any asymptomatic individuals. So it was easy to stop the disease before it spread (artificially lowering the R0 effectively).
However the COVID-19 has a large portion of people with the disease whoa re asymptomatic. This causes the spread to go unhindered. Despite having a lower R0 and lower mortality rate the death toll is already more than 10x what it was for 2002 SARS.
The numbers are scary, it suggests to me, we are in for some really nasty times ahead...
Death rate (global): 6%
Death rate without any previous condition: 0.9%
Death rate for people below 50 years old (no previous condition): 0.3-0.4%
@proxeus So much invalid data framing there I dont know where to start... What scholarly source did you get that from, I would be very shocked if any such source would frame data in that way.
The link you posted doesnt agree with any of the numbers you just posted either.. it clearly states the mortality rate was 7% (the number I stated) not 6% as you just stated, furthermore the number "0.9" does not show up anywhere on that link at all. Nor do any of the other figures you stated.
This is all taken from official data.
@proxeus Ahh I see how you got such misleading data then..
Your percentage for all people under 50, for example.. aside from being a very arbitrary line to set, it also is invalid because your calling from data on "suspected cases" rather than "confirmed cases" which your dataset has no data for apparently. Obviously false positives by simply visually diagnosing someone is **huge** for a pandemic where peope are in fear. So those numbers are almost entirely invalid.
Though you will find of the people who have died fromt his disease about 80% are people who are older or who are comrpomised in some way. But that really doesn make it any less severe. We see that sort of pattern with most diseases like the flu, yet the spanish flu was still capable of killing 100 million and the 2009 swine flu capable of killing half a million. So not really a counter argument regardless.
"We will list data from both, labeling them as "confirmed cases" and "all cases" respectively in the tables."
Which means it includes CONFIRMED cases as well as suspected, which means the rate might even be lower anyways because it's including more people than it should...
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