Groups | Search | Server Info | Keyboard shortcuts | Login | Register [http] [https] [nntp] [nntps]

Groups > misc.consumers > #20719

Re: Looking at Covid19 data

Show all headers | View raw

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.

Back to misc.consumers | Previous | Next — Previous in thread | Next in thread | Find similar | Unroll thread

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

csiph-web