Posted on 04/03/2020 6:22:30 AM PDT by SeekAndFind
Easter is my target too. If you plot the cumulative deaths in the US on a semi-log chart it’s a straight line so you can project it. When this line crosses the 50,000 mark it has to tip then to hit the 100,000 total. I assume as it winds down the total from that point will be equal the the run-up total ( normal curve ). Same is true for the 200,000 total the tipping point has to be around 100,000 cumulative total.
The first date is 4/10 and the second date is 4/13.
I like to avoid blaming the messengers standing in front of negative clueless media people. This thing has to run its course and there is little we can do to change its course or effect.
I am tracking the CDC data on a daily basis. The infection rate is slowing. You may very well be right.
Well people better get to it. To get from 5,000 to 200,000 is a lotta dyin.
I just think people will get tired of it.
On my daily walks, I already see more traffic
So, I think a key question should be asked:: Are those presently dying actually canaries, or are they in fact the caboose?
If we segment the main population as young (school children), adults (working, vacationing), and 'at risk' (older, pre existing), who typically comes into contact first with communicable disease? The middle, right? They come into contact first because they are constantly traveling (local, regional, international), dealing with 10/100s of (new) people every day, shaking hands, dining, socializing, etc.
So, why didn't the great middle get sick (and die) first? Or, did they - just get sick, that is? If those older, pre existing patients who are dying are canaries, how did they precede the middle in contacting the disease? Sure, some older folks go on cruises, but compared to the millions of people coming/going out of airports each day (work, leisure), it's a micro bit.
Conclusion: If the great middle got the virus first, then the die off we're currently experiencing is the caboose. IOW, the tail end of the (invisible) infection wave.
Experts tend to hate anecdotal 'evidence', but there are so many people (like myself) relating how we were very sick during Jan-Feb. I never felt sick-sick, and it never kept me down, but everyday I'd have to clear my lungs from some kind of mysterious lung congestion.
Now Cuomo is stating that he thinks New York may have had CV back in Nov. That's great, because I was in NYC for a week before T-day, and guess who actually got sick-sick shortly after his return to sunny SoCal? (I was completely ok until the mysterious hacking, non-illness appeared 8 weeks later.)
So many questions, so many assumptions. What we really need is an anti-body test, and broad based population sampling to determine past & present levels of infection. "Cases" is still bandied about, even though there couldn't be a less valid statistical measure possible.
circles and arrows, and hockey sticks, and don’t forget the colors, lots of them, and got’s to have exponential in there someplace, and the fact that hayseeds don’t have a grasp of that.
Ding! Ding! Ding!
Wow, flip that over and rotate, looks strangely familiar!
No one knows right now. It will be known in a year or so. I would think. Will WE know is a different question.
And we must remind ourselves that we are looking backwards in terms of the positive cases who contracted the virus one or two weeks ago. We should start seeing the effect of the lock downs and other preventative measures.
Bookmark, very interesting comment.
Would be interesting to get an antibody test ran.
This was in mid Feb.
Spread to wife and daughter, although theirs was somewhat milder.
The models and predictions are all baloney. There is no way to know how many will die as the number of variables are massive. They are just guesses.
Is it true Fauci wants the lock down to continue until the very last case of COVID 19 is detected?
Exactly. So why are the public health officials getting it all wrong?
I’m still sticking with 40,000 dead until events say otherwise. We can’t even put a number on the total cases. I think the idea everyone will get it might be pure fantasy, as social distancing, population density, ect, will reduce that assumption. To what Who know? No one knows.
This is the one time the cry wolf fable fails. You would think after epidemic after epidemic the population would become hardened. Nope. Every time they eat up the media BS like its cup cakes. Every time they freak out and only hear the worst case scenarios.
Modelling 101:
WARNING: This is not for journalists or democrats, who are not capable of understanding math.
Remember algebra?
x+y=2
x-y=0
solve for x and y.
Remember that you for two variables you needed two equations to solve.
For three variables you needed three.
Etc. Etc.
Now lets get a little more complicated:
Solve for all the variables in these equations.
2x+4y-cosz+3w(r+2s-4t)=85
(cosx+siny)(2z-14w) + 2r+12t=15
You can’t - you need 7 equations for 7 variables.
Well, that’s what you need to do when you are modelling complex phenomena, like weather, climate, corona virus, etc - many variables, not enough equations.
So you make assumptions, like “make t a constant” or assume r+s approaches 0.
Of course it gets more complicated than that, with other goodies like partial differential equations and complex math functions, but that’s the essence of modelling.
In some cases you get answers close enough to the solution to be workable and useful, like the hurricane model definitely will hit Florida, but you can’t say exactly where, but the people of Texas know enough to have a sigh of relief.
Now if the model wrongly assumes or ignores one or more of those variables, like the age demographic component or the dietary levels of vitamin z, the model becomes meaningless.
Bureaucrats then have to resort to coming up with other guesses and excuses, to look good, and to bamboozle an ignorant media, using terms like “leveling the curve” or “hockey sticks”.
Welcome to Modelling.
By the way - my coronavirus model?
In the USA, 36,326 dead, 498,603 infected, and 35 democrat congressmen voted out of office.
A friend of mine, when I lived in Florida, worked for a phosphate mining company. One of his jobs required he file models to the state environmental board which projected their holding ponds’ ability to meet state standards for the up coming year if they wanted to keep mining. A major dependent variable was how many inches of rain would fall.
If the model’s results did not meet state specs, he would change his estimate of predicted rainfall by a tiny amount and, bingo, the model met the environment board’s standards and then it was business as usual.
This goes on all the time in countless public and private sector situations. And it’s not necessarily fraudulent. In cases like his, the government requires he pull a number out of thin air rather than say “we just can’t predict”. Bureaucrats refuse to accept that notion. They believe that everything can be quantified. It is essential to their mindset of infallible central planning. Which histoy shows never works.
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