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Why You Need to Pay Attention to the Coronavirus: Analysis & Numerical Predictions

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“Why You Need To Pay Attention To The Coronavirus: 
Analysis & Numerical Predictions”
by Relik
“It’s unfortunate that people aren’t understanding that the fatality rate is very high at 3%. That doesn’t sound like much?
A) The regular seasonal flu in December infected 13 million in the US and killed 6,600. On a numbers basis, that sounds much worse than this coronavirus they are scaring us with, right? 1 person died out of every 1,969 people infected.
B) With this coronavirus, 1 out of every 33 people infected are dying. See the problem? If the same 13 million people in the US got this virus in a month, 390,000 would die.
C) Next month another 10 million may get it, another 330,000 dead. The month after that it might mutate and EVERYONE once again is subject to a 3% chance of death if they get it.
D) It is very likely and only a matter of time that this number of people may contract the virus in the US. With a current estimated Ro of 3.8 – 4.0, it is twice as infectious as the seasonal flu. Again, do I need to remind everyone that the seasonal flu infected 13 million people in December alone?
E) Go ahead and try to locate a simple bare minimum N95 mask right now. I checked online at Home Depot, Lowe’s, Wal-Mart and others and every single store has limited or no stock. They are not purchasable via their online sites. I ended up buying some at Amazon for early February delivery. No one in the US has even died yet and there are already no masks available!
F) According to a Youtube video I watched, they say Chinese drop shippers in the US have purchased massive numbers of N95 masks and are sending them back to China to make a profit.
G) I made a spreadsheet after using the official Chinese data of 17 cumulative deaths on Jan 22 and 25 cumulative deaths on Jan 23. I made this on January 23rd. 
On January 24th, China announced 41 cumulative deaths. Do you see that this is even higher than my predictive function below indicated (37)? This predictive function increases at a very simple exponential rate – every day take the cumulative people that have died and over the next 24 hours 1/2 again as many people will die. The scary thing is this has proven true so far.
1st column “Date” – Numbers taken late evening Eastern time.
2nd column “Cumulative worldwide deaths”.
3rd column “Deaths over next 24 hr period”.
4th column “Official count when available” – Post will be updated/
Jan 22:  17 – 8 – 17 official
Jan 23:  25 – 12 – 25 official
Jan 24:  37 – 18 – 41 official
Jan 25:  55 – 27
Jan 26:  82 – 41
Jan 27: 123 – 61
Jan 28: 184 – 92
Jan 29: 276 – 138
Jan 30: 414 – 207
Jan 31: 621 – 310
Feb 1:   931 – 465
Feb 2:   1,396 – 698
Feb 3:   2,094 – 1,047
Feb 4:   3,141 – 1,570
Feb 5:   4,711 – 2,355
Feb 6:   7,066 – 3,533
Feb 7:   10,599 – 5,299
Feb 8:   15,898 – 7,949
Feb 9:    23,847 – 11,923
Feb 10:  35,770 – 17,885
Feb 11:  53,655 – 26,827
Feb 12:  80,482 – 40,241
Feb 13:  120,723 – 60,361
Feb 14:  181,084 – 90,542
Feb 15:  271,626 – 135,813
Feb 16:  407,439 – 203,719
I’m not going to show you further data because I predict the exponential function will slow down at this point. I also don’t want to predict that tens of millions of people may die.
If you don’t believe me, save this post and come back to it in a few days. If on January 27th China has reported more than 123 deaths maybe you will start to grasp the situation.
You need to be warned though that China might start to really manipulate the numbers when the deaths start getting high. For all we know they are already grossly underreported.”
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