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Re: Looking at Covid19 data

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On 5/27/2020 5:25 PM, root wrote:
> RosemontCrest <rosemontcrestwinery@post.com> wrote:
>>
>> Pay no mind to Bob F. It actively participates in off-topic, political
>> discussions on alt.home.repair, thus destroying that newsgroup with
>> unrelated politics. Notice that it is the one who introduced politics to
>> this discussion about scientific data analysis.
>>
>> I am interested to see more of your findings. Are you willing to share
>> your data?
>>
> 
> The data I work with is publicly available at:
> https://github.com/nytimes/covid-19-data/archive/master.zip
> Which includes data for the US as a whole, every state and
> territory, and every county. Lots to chew on.
> 
> I don't want to post if there is no interest.
> 
> I will abandon the approach I started to take in favor
> of a more important and easier thread to follow.
> 
> The above source reports a daily account of number of reported
> cases and number of deaths. For some time I have wondered how
> may people have actually been infected when some lesser number
> is reported. Let's say that when X cases have been reported
> there are really M*X people infected. Can I squeeze M out of
> the reported data. I think I can.
> 
> Here is the basic plan:
> 1. for any given data set compute the daily differences of the
> 	number of cases.
> 2. divide these daily differences by the corresponding number
> 	of cases.
> 3. compute the variance and SD of the daily differences.
> 
> 	There is a trend to the daily differences and
> 	that trend has to be removed or corrected before
> 	computing the SD.
> 4. compute the expected variance and SD of the daily
> 	differences.
> 
> 	I will show how the expected SD is computed below.
> 5. The ratio of the first SD to the second SD is my
> 	best estimate of M.
> 
> I was motivated to consider this approach because the
> SD of the daily differences was too large to be
> explained.
> 
> In step 2 we divided the daily differences by the
> number of cases to-date. What does this number
> mean? Let C be the number of cases and deltaC be
> the daily change.  I assert that deltaC/C is the
> probability that one of the C cases will infect
> a new person in the next day. This is a binomial
> probability (p)  and, for a large value of C, we can
> approximate the SD of the number of new cases by
> a normal distribution with SD=sqrt(p*(1-p)*C)
> Tyoically this is a few hundred cases. In contrast
> the SD from step 3 is a few thousand cases and
> the ratio (M) is a number on the order of 10.
> 
> I have computed the values for each of the states
> and territories and the value for the US is 14.5 or
> so. There is a discrepancy in that number which
> I am investigating. Whatever the value of M,
> the lethality of the Sars-Cov2 virus as determined
> by deaths/cases is reduced by the factor M. If
> M were 14.5 and deaths/cases was 4% then the
> revised lethality would be .275% which is less
> than 3 times that of ordinary seasonal flu.
> 
> The number M is vitally important.
> 
> There are still some things about the procedure that
> bother me. I use my own software for all this, but
> I have a friend who uses Excel to do the computations
> at his end.
> 
> If you are familiar with Excel you can easily bring
> up the data an have a look for yourself. Get back
> here if you have any questions, and if you tire
> of this let me know as well.
> 
> Thanks.

Thank you for the link. I remain interested and hope that others express 
interest. Presenting more findings and discussion may garner more 
interest. Please continue to pursue and share your endeavor.

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Thread

Looking at Covid19 data root <NoEMail@home.org> - 2020-05-25 20:33 +0000
  Re: Looking at Covid19 data RosemontCrest <rosemontcrestwinery@post.com> - 2020-05-25 15:01 -0700
    Re: Looking at Covid19 data root <NoEMail@home.org> - 2020-05-25 23:18 +0000
      Re: Looking at Covid19 data RosemontCrest <rosemontcrestwinery@post.com> - 2020-05-25 16:25 -0700
        Re: Looking at Covid19 data root <NoEMail@home.org> - 2020-05-25 23:42 +0000
          Re: Looking at Covid19 data root <NoEMail@home.org> - 2020-05-26 00:27 +0000
            Re: Looking at Covid19 data Bob F <bobnospam@gmail.com> - 2020-05-25 20:15 -0700
              Re: Looking at Covid19 data RosemontCrest <rosemontcrestwinery@post.com> - 2020-05-27 14:15 -0700
                Re: Looking at Covid19 data root <NoEMail@home.org> - 2020-05-28 00:25 +0000
                Re: Looking at Covid19 data RosemontCrest <rosemontcrestwinery@post.com> - 2020-05-27 22:02 -0700
                Re: Looking at Covid19 data root <NoEMail@home.org> - 2020-05-28 14:44 +0000

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