Consider deaths in Louisiana (20) vs. Texas (90).   Both states with lots of 
obesity and similar weather.  

-----Original Message-----
From: Friam <friam-boun...@redfish.com> On Behalf Of u?l? ?>$
Sent: Wednesday, August 11, 2021 10:52 AM
To: friam@redfish.com
Subject: Re: [FRIAM] off-label technologies, exaptatiion and exponential 
technological growth.

It would be interesting to plot some geographical data about comorbidities, 
particularly obesity.

On 8/11/21 9:09 AM, Marcus Daniels wrote:
> It is weird there are orders of magnitude of variability.   I wonder if it is 
> differences in spatial distribution of the different vaccines?   Ethnicity?   
> Prevalence?
> -----Original Message-----
> From: Friam <friam-boun...@redfish.com> On Behalf Of u?l? ?>$
> Sent: Wednesday, August 11, 2021 8:06 AM
> To: friam@redfish.com
> Subject: Re: [FRIAM] off-label technologies, exaptatiion and exponential 
> technological growth.
> 
> Attached.
> 
> Missing Arkansas, Connecticut, Florida, Hawaii, Iowa, Kansas, Maryland, 
> Missouri, New York, Pennsylvania, West Virginia, Wyoming.
> 
> On 8/10/21 4:43 PM, David Eric Smith wrote:
>> I am sure it is just dieseling at this point, but I was pleased to see the 
>> following article:
>> https://www.nytimes.com/interactive/2021/08/10/us/covid-breakthrough-
>> i
>> nfections-vaccines.html
>> <https://www.nytimes.com/interactive/2021/08/10/us/covid-breakthrough
>> - infections-vaccines.html> (I usually get to these things late; 
>> y’all probably have read it already)
>>
>> In reading the first table, on hospitalization and death fractions by 
>> vax/unvax, I was thinking “okay, now since we have vaccinated 
>> fractions by date, we could do a covariance plot, and of course could 
>> then do more involved multiple regressions on dummy variables as we 
>> could find them.”  (No pun meant on “dummy variable”, though I am 
>> unable to miss it myself.  Things like measures of hospital 
>> performance, coverage of masking rules or other public health 
>> measures, population density and gathering density, etc.  Some of 
>> these to be proxies for fraction exposed, which is hard to get at.)
>>
>> But then that is just where the article goes.  It’s funny how a pair made of 
>> a careful writer and a lazy reader can be an unhelpful combination.  The 
>> text leading to the second table says "people who were not fully vaccinated 
>> were hospitalized with Covid-19 at least five times more often than fully 
>> vaccinated people, according to the analysis, and they died at least eight 
>> times more often.”  I remember the nice passage in John Paulos’s book 
>> “Innumeracy”, where (to make some point, which I now forget), he comments on 
>> why a sign over the highway “Entering New York, Population at least 6” is 
>> not particularly informative, though quite true.
>>
>> Look then at the distribution of multipliers in the table.  For the “at 
>> least five times” column, the first six entries, alphabetically, are 75x, 
>> 17x, 47x, 68x, 22, 148x, 161x, and likewise for the “eight times” column. 
>> Ahh, if the American Public would only tolerate being shown a histogram 
>> giving the whole distribution at a glance….  Of course, if I were not lazy, 
>> I could find and download the data and make my own histogram.
>>
>> But, credit to those authors.  Within the bounds of what is permitted to 
>> them, this is a useful data digest.
>>
>> Eric
> 
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