@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.

@proxeus My source is varied and many as I cited a lot of different data for different epidemics (as a data scientist I've been doing a lot of research on this).. For the COVID-19 data specifically I sourced that from the live data provided by John Hopkin's University.

@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.

@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.

@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.

@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.

@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.

@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:

https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports

https://www.cdc.gov/coronavirus/2019-ncov/index.html

https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases

http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml

https://3g.dxy.cn/newh5/view/pneumonia?scene=2&clicktime=1579582238&enterid=1579582238&from=singlemessage&isappinstalled=0

@proxeus Also keep in mind the numbers reported by china up to and include Feb 12th were later found to be invalid. The global data sets after that data had to be significantly adjusted to reflect the correct numbers. So any data out of china prior to feb 12th has inaccurate data.

@proxeus @freemo While I am familiar with these numbers, CCP has been kinda shoddy in what constituted a Corona infection/Death. I see them more as an indication of things to come than anything else.

@xyfdi

These arent numbers fromt he CDC, the numbers in that table come from china, prior to it being discovered they were underreporting their data. So the data in that table is no longer considered valid. See my post where I link to up to date sources instead.

@proxeus

@KatGoesWoof

All true.

Thought keep in mind what "putting the virus in check" means.. Our best efforts now will slow down the epidemic. This is a good thing because as you said there are a limited number of beds and a shortage of hospital staff. So if you can spread the disease out over a longer period of time then we wont go over-capacity and more people live.

But its important to note that those measures, while they may save some lives, it wont reduce the number of people who get effected. The virus is out int he wild now, there is no reversing that.

@KatGoesWoof I wouldnt say cant, but its very unlikely.

Its spread to far too many regions to be able to stop it by quarantine, that is literally impossible at this point. Especially because many carriers of this disease are asymptomatic which makes quarantining useless.

The only way you could possibly stop it is via immunity. That means either you catch the disease and live through it (which I wouldn't call stopping it considering the 7% mortality rate) or a vaccine.

A vaccine is possible but very unlikely. There are several Coronaviruses that have been in the wild for some time now. Four of which are so common virtually every adult has caught them. Some are less common but far more deadly, like SARS. Despite this no one has ever created a safe and effective vaccine for a virus int he corona family of viruses. So it is unlikely they will find one for this. But maybe...

@KatGoesWoof Yes in fact many have went far beyond COVID19 in terms of how widespread they are.

10% - 20% of people who think they have the common cold are actually expierncing a type of corona virus. More specifically one of four strains of coronavirus that present similar to the common cold. As you can imagine they are as wide spread as the common cold.

But even though they are widespread they dont tend to kill people. So dont worry too much.

SARS virus is also int he Coronavirus class, it has never become widespread though.

@KatGoesWoof The reason the other coronaviruses were never an issue has less to do with how they spread and more to with the fact that they just dont tend to kill people.

Obviously they have spread to a much larger portion of the population than COVID19 has.

@freemo @KatGoesWoof Hi. Doesnt the virus need a warm human host to survive? (I heard it died after 12 to 24h)

So it would die in the nature if we are all home. And if we are all home, after 2 weeks it will be quite clear who's been infected and who's not, making it much easier for sane people to not get infected. No?

Then we'd have to lockdown all sick people to keep it contained, if the number is not too huge..

Seems a hard task indeed

@Luna

Yes and no. It does die in nature like most viruses. But everyone quarantining will not stop it for a few reasons.. 1) you only need a single infected person for it all to startup again, remember this started with just one person 2) there are a large number of asymptomatic carriers so even after quarantine you wont know who has it and who doesnt 3) the quarantines are self imposed and people still gather in small groups.

Quarantine is not, and never was, about reducing the number of people who get effected throughout the whole epidemic, that number will be the same no matter what at this point (the herd immunity point for the population). It was always about spreading out the pidemic and cases over a longer period of time to not overload healthcare facilities.

@KatGoesWoof

@snow We dont, these are just the current best estimates. The R0 is more a lower bound in that sense

@snow Its possible

@esureL The currect estimated mortality rate is actually 3%, but your right no one really knows yet. The 7% mortalty rate is only the rate recorded, not the actual rate. Reporting practices need to improve.