Fiasco in the making?

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LADoc00

Gen X, the last great generation
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Personally I think I lost all perspective on what is happening here, momentarily caught up in the madness of the public panic where I am located.

Now 3-4 drinks into the night, I am very concerned this is a total fiasco in the making. Not that is this nothing but that the healthcare apparatus is grossly overreacting out of all proportion to reality.

Just read this from Stanford:

From: Meta-Research Innovation Center at Stanford (METRICS) at Stanford University.

This evidence fiasco creates tremendous uncertainty about the risk of dying from Covid-19. Reported case fatality rates, like the official 3.4% rate from the World Health Organization, cause horror — and are meaningless. Patients who have been tested for SARS-CoV-2 are disproportionately those with severe symptoms and bad outcomes. As most health systems have limited testing capacity, selection bias may even worsen in the near future.


Projecting the Diamond Princess mortality rate onto the age structure of the U.S. population, the death rate among people infected with Covid-19 would be 0.125%.
(Swine flu by comparison is thought to be 0.02%)

In an autopsy series that tested for respiratory viruses in specimens from 57 elderly persons who died during the 2016 to 2017 influenza season, influenza viruses were detected in 18% of the specimens, while any kind of respiratory virus was found in 47%. In some people who die from viral respiratory pathogens, more than one virus is found upon autopsy and bacteria are often superimposed. A positive test for coronavirus does not mean necessarily that this virus is always primarily responsible for a patient’s demise.

If we assume that case fatality rate among individuals infected by SARS-CoV-2 is 0.3% in the general population — a mid-range guess from my Diamond Princess analysis — and that 1% of the U.S. population gets infected (about 3.3 million people), this would translate to about 10,000 deaths. This sounds like a huge number, but it is buried within the noise of the estimate of deaths from “influenza-like illness.” If we had not known about a new virus out there, and had not checked individuals with PCR tests, the number of total deaths due to “influenza-like illness” would not seem unusual this year. At most, we might have casually noted that flu this season seems to be a bit worse than average. The media coverage would have been less than for an NBA game between the two most indifferent teams.

full article:

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I think where you are really off is the % infected. If this cannot be contained and we stop preventative measures, the estimated exposed rate might be 80% before herd immunity protects the rest.
 
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Where does the 1% infection assumption come from?
 
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Through yesterday, CA reported 1733 positive cases and 12,100 negative cases, with 27 deaths. AFAIK, there is no screening in place, so it is not clear how representative these data are. These numbers are from the California Department of Public Health.
 
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I will also add that the suspected incubation time of this virus is about 4-5 days. It is a small sample size, but if you look at the data in 5 day increments we are still growing exponentially by deaths attributed to this disease
 
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Where does the 1% infection assumption come from?

It is an assumption Stanford data center made based on better epidemiological data than initially folks were working with.

Is this correct?? I have NO clue, but this contrarian research paper has me very very concerned about our response to this (in addition to the actual virus itself).
 
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