Some Hard information on 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...

@freemo https://www.worldometers.info/coronavirus/

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.

@freemo Sorry, that's official data issued by the government of each country, and the ratios are actually statistics from this data. The ratios I mention are here: https://www.worldometers.info/coronavirus/coronavirus-age-sex-demographics/

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.

@freemo "A paper by the Chinese CCDC released on Feb. 17, which is based on 72,314 confirmed, suspected, and asymptomatic cases of COVID-19 in China as of Feb. 11"

"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...
image.png

@proxeus No the fact that it includes confirmed and suspected cases means the actual number is **higher** not lower.

simple logic should tell you that, If they suspect 100 people have COVID19 and only 10% actually have it and the other 90% just have ordinary flu. then you'd see a mortality rate that is the weighted average of the flu and of COVID19 with the flu being weighted 9x higher than COVID19 in that imaginary scenario. The flu has a mortality rate of about 0.02% - 0.04% comapred to the COVID19 mortality rate currently at 7%.. so you can see how including suspected cases that turn out to be flu would LOWER the mortality rate, not increase it.

@freemo It's not because if someone dies from pneumonia, it still counts in this case even if the pneumonia was caused for another reason not related to the virus, but since they might have thought it's the virus, it's included in the statistics, and thus, it's adding noise to it. Therefore the ratios might be higher than they actually are for that study.

In any case the absolute death rate is no higher than 6-6.5% (It's currently a 6.35% rounded to 7%, look at the values in the graph) which is the actual observed rate. Mostly elder people or people with a previous condition.

@proxeus No your forgetting that if someone **survives** pnumonia but they were suspected of having COVID19 they also wind up int hat chart, which lowers it.

Since very few viruses have the mortality rate of a SARS virus, in this case 7%, any viruses accidentally included in suspected cases will lower the mortality rate rather than increase it. Your forgetting that both those who survive and those who die are factored into the mortality rate.

@freemo And you're forgetting that this is all official data and that your fear spreading is taking us nowhere. It's all in the data and statistics. The chance of surviving the virus is actually pretty high.

@proxeus I'm spreading the actual data from actual sources.. There is cause for some level of fear, feat is what keeps you alive and encourages you to be safe, so in that sense the fear is healthy, because the official data (which I shared) is very real.

You can wish and hope and lie to yourtself all you want that this isnt a serious epidemic, but you arent helping anyone by doing that...

But yes, there is a very good chance you will survive, no doubt. The spanish flu killed 100 million people and its mortality rate was even less at 2.5%. If you lived during the spanish flu you had a good chance of surviving too, but that doesnt make it any less of a tragedy nor the fear of the people at the time any less legitimate.

@freemo The official data I linked is the actual data. There is nothing else. Fear only leads to unreasonable actions, and unreasonable actions take us to error and failure, and thus, we might suffer more than we should. This is no time for fear. We need to keep our heads cold.

@proxeus We were both pulling fromt he official data. The difference is I was pulling from scholarly sources and using my expertise as a scientist to understand how to frame that data.

As we covered you however pulled from a valid data source, but you then proceeded to do your own math and draw your own conclusions out of it that were ultimately shown to be invalid as I just recently explained why.

The issue isnt the data, its the fact that you dont understand how to actually analyze the data in a way that you can draw useful conclusions from it.

@freemo Your "expertise" didn't let you see what I said about all that data being stated in that page and that all the information about where it was gathered is there while you didn't even provide a source other than "I took it from a school" and "I'm an expert, I know what I'm saying".
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@proxeus

1) are you even listening, yes I did and specifically addressed why your interpritation was faulty.. The data is only partly faulty as we covered the data from china prior to feb 12th has since been adjusted and redacted.. so yes, it is faulty.. second the math and conclusions you drew were also incorrect even if the data happened to be correct, I already explained why

2) no i gave the specific source of the data, the live data provided by John Hopkins University. Though I did indicate it was compiled from multiple sources for completeness. Here are the specific sources the data set is merged from:

who.int/emergencies/diseases/n

cdc.gov/coronavirus/2019-ncov/

ecdc.europa.eu/en/geographical

nhc.gov.cn/xcs/yqtb/list_gzbd.

3g.dxy.cn/newh5/view/pneumonia

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