[ExI] bikers again

Henry Rivera hrivera at alumni.virginia.edu
Thu Aug 26 11:37:54 UTC 2021


About Sturgis this year and last:

South Dakota COVID cases explode after Sturgis motorcycle rally
https://www.alternet.org/2021/08/south-dakota-sturgis/

“In 2020, the event was such a massive superspreader that 5 million cases could be traced back to the rally.“

> On Sep 4, 2020, at 7:14 PM, Henry Rivera <hrivera at alumni.virginia.edu> wrote:
> 
> We do that in Mass. But I see your point that all places should do so. The Feds could strong-arm standardization among the states by, say, making some funding contingent on it. We need(ed) better leadership for that to have happened if you ask me. 
> 
> <image0.png>
> 
> 
>> On Sep 4, 2020, at 5:30 PM, spike jones via extropy-chat <extropy-chat at lists.extropy.org> wrote:
>> 
>> 
>> 
>> -----Original Message-----
>> From: Henry Rivera <hrivera at alumni.virginia.edu> 
>> Sent: Friday, September 4, 2020 2:12 PM
>> To: ExI chat list <extropy-chat at lists.extropy.org>
>> Cc: spike at rainier66.com
>> Subject: Re: [ExI] bikers again
>> 
>> What does this refer to specifically?
>> 
>>>> On Sep 4, 2020, at 4:08 PM, spike jones via extropy-chat
>>> <extropy-chat at lists.extropy.org> wrote:
>>> and the failure to break out nursing home deaths,
>> 
>> 
>> Hi Henry, take all covid fatalities, separate all those who lived in a
>> nursing home or long term care facility.  List the numbers separately.
>> Here's an example of where that is being done:
>> 
>> https://www.sccgov.org/sites/covid19/Pages/dashboard-cases.aspx
>> 
>> This is useful information.  The green bars are nursing homers.  Looks like
>> about half of the fatalities are there, and we already know the really
>> super-annuated almost all live in a nursing home.  But if we treat those as
>> two separate groups and do our demographics similarly, the risk to older
>> non-nursing homers isn't nearly as disturbing, and Henry there is a reason
>> why I keep going on about that.
>> 
>> Any distortion of the risk picture introduces new risks.  
>> 
>> For instance... my father's second cousin is one of my genealogy partners.
>> He lives practically within walking distance of the hospital where I was
>> born (he was born there too) and has never moved.  It is a small hospital:
>> everybody knows everybody there.
>> 
>> When the covid emergency began, many regular customers stopped coming.  My
>> cousin continued but he isn't afraid of much (he faced the Viet Cong in
>> 1963, a virus doesn't scare him.)  Not enough customers, the hospital had to
>> close its doors.  He didn't re-establish contacts at the hospital over in
>> the big city.  His prescriptions ran out.  Fluid built up around his heart,
>> he wound up in the ER at the hospital he had previously refused to
>> patronize, hoping for the best with his congestive heart failure.
>> 
>> He survived after a really bad night hooked up to the old blibbity beepers
>> (his term (wonderfully descriptive (not overly technical (but everyone here
>> knows what he means.))))
>> 
>> But otherwise he would be an example of a patient who died OF covid WITHOUT
>> covid.
>> 
>> Distortion of the risk matrix introduces new risk.
>> 
>> spike 
>> 
>> 
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