Posted on 04/12/2020 3:29:24 AM PDT by Oldeconomybuyer
State leaders are relying on a hodgepodge of statistical models with wide-ranging numbers to guide their paths through the deadly coronavirus emergency and make critical decisions, such as shutting down businesses and filling their inventory of medical supplies.
During hurricane season, coastal states can trust the same set of computer models to warn of a storm’s track. During this pandemic, there is no uniform consensus to predict the toll and direction of the virus that is tearing through communities around the country.
With little agreed-upon information, governors and local officials are basically creating do-it-yourself sources of information with their own officials and universities.
The models have resulted in conflict in several locations.
The federal government and many states rely on a University of Washington model that’s the closest thing to a benchmark but it is so imprecise that the latest projection for the death toll had a range of more than 100,000. In Washington D.C., health officials took the unusual step of publicly announcing that they didn’t trust the University of Washington’s updated model and embraced far more pessimistic predictions from a model created by researchers at the University of Pennsylvania.
Some states, including Alaska, Ohio, Pennsylvania, Minnesota, Louisiana, are incorporating the work of local researchers and other experts to fine-tune their models.
Some elected officials have cited the most dire forecasts in issuing stay-at-home orders. Others have seized on more optimistic figures from their models to justify their calls to loosen restrictions.
(Excerpt) Read more at apnews.com ...
Ahh..so this current Coronavirus epidemic will follow the pictured paths. /sarc
Stopped reading right there. You can't fix stupid.
You're telling me.
translation: Oh, sh*t, they might actually recall Gretchen Whitmer.
Only way to read the AP is between the lines.
Me too!
Here’s a question: Why didn’t swine flu shut down the country in 2009..?
Different prez? Trump vs Obama?
Different vics: kids vs reliably Dem voters?
What’s changed and why?
Any journalist who thinks the "same set" of computer models used to predict weather is also used to predict health is beyond stupid. That's the first two sentences. Read no farther.
Hurricane models have a long history ...they give you the general area..
The general area if the corvid16 models
2,0000,0000 or 50,000
It’s time to open the economy ....
Trump needs to it this week ....
It will be up to each governor after Trump says go ahead
So you know the economy will never recover
There has to be no social distancing required..
It is fear that will drag on fore a long time
The press will count the dead every day...
So forget the economy getting better fast
They tested US folks for swine flu and almost nobody had it—so they knew early on the gloom and doom models were total garbage.
The test is the key—if it is valid we have a big problem—if it is not valid we have another big problem. :-)
You need to change your example...H1N1/Swine flu had 12K fatalities over a year in the US...COVID-19 has 20.5K fatalities in 6 weeks. H1N1 was kind of a dud as far as flu goes.
H1N1’s 60 million infected is rather a lot to my mind.
As for death tolls, how do we know for either?
Is dying while positive the same thing as dying of the ailment?
The one thing we are certain of is that the two epidemics not being handled the same.
I think it would be very instructive to know why.
H1N1’s 60 million cases were a lot, but “only” 12.4K fatalities from it made it kind of a “dud”. Epidemiologists saw that rate and said “less than regular flu” so no draconian measures taken. In comparison the 2017-2018 flu season in the U.S. had about 45 million cases with 61K fatalities...a lot worse than H1N1.
As for “death tolls”/mortality rates/CFR’s, it all depends greatly on how many people have had/currently have the disease. I can make the case for “COVID-19” is a “nothing burger” if I use the current rate of positive tests done nationwide (~19%) that would mean that about 64.8 million Americans have had COVID or currently have COVID...making the “death rate” very low (lower than regular flu)(0.03%)...but of course using that math is not accurate due to the testing primarily being done on “suspected cases”. If you use a “educated guess” for the # of people that have had COVID (3%-5% nationwide) added to the current cases then you get 0.215% (2x as bad as reg. flu) to 0.129% (about the same as a bad year for “regular flu”). If you use the “currently known cases” number (~557K) you get a fatality rate of 0.39% or about 4x worse than reg. flu. As you can see a case can be made for “this is overblown” using one set of suspect numbers, and an equally “good” case can be made that “this is 4 times worse than the regular flu”. Personally my current thinking is that COVID-19 is tracking at about a 0.19%-0.2% fatality rate based on about 10 million people in the US having had or currently having COVID (just under 3% of the pop.) and the current # of fatalities. (21,956/10,000,000).
As for “dying while positive” it is not that hard for a county coroner to determine COD for COVID-19 as most all the fatalities are on a respirator with fluid on the lungs, viral pneumonia and a low O2 level causing organ failure at the time of death. Regardless of other underlying conditions like cancer, etc..
As I mentioned at the beginning of this post H1N1’s CFR was determined to be pretty low (lower than “normal flu”) early on in the outbreak resulting in it not being “panicked” over.
https://www.cdc.gov/flu/pandemic-resources/2009-h1n1-pandemic.html
https://covidtracking.com/data
https://www.worldometers.info/coronavirus/#countries
https://www.cdc.gov/flu/about/burden/index.html
A bad disease model cost us two trillion dollars and 22 million jobs. And liberals are screaming, “But give us more of this power, we’ve got climate models predicting the end of the world!”
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