On 10/4/20 11:21 am, Bernard Robertson-Dunn wrote:
Here's a much more useful description (in the current circumstances) of
what's going on than any of Dr Jansson type models
The one COVID-19 number to watch
https://www.abc.net.au/news/2020-04-10/coronavirus-data-australia-growth-factor-covid-19/12132478
It's a great reductio ad absurdum.
Pity it's dated 10 April, rather than the morning of 1 April.
Like all simplistic single-data-item representations of complex
real-world systems, it's so useless it's laughable.
They don't declare a model, just a formula:
"Calculating the daily growth factor is as simple as taking today’s new
reported cases and dividing it by yesterday’s new cases"
And the model that's implicit in that formula is limited to daily
snapshots of one small element of the Susceptible, Exposed, Infected,
Recovered (SEIR) notion. (They appear to mean by 'cases' something like
'that subset of Infecteds that have been noticed and recorded').
And, as per my email of 08:57, even the SEIR notion is insufficiently
complex to provide a basis for useful modelling; so the Elvery et al.
tiny sub-set of SEIR is just plain silly.
And that's only the *modelling* aspect of their proposal. Even if the
model made some kind of sense, the data it depends on is utter nonsense.
Editing a para. from my email of Fri, 3 Apr 2020 18:15:30 +1100:
> 'Case numbers' is a meaningless metric, because it's impossible to
know what each day's count means, it adds apples and oranges, and none
of it tells anyone anything useful.
Editing some text from my email of Fri, 3 Apr 2020 11:49:04 +1100:
> Countries have adopted very different approaches to recognising
cases, and have changed their approach over time and space, sometimes
frequently.
>
> Mostly, the sample of the population that is being tested at any
given time is intentionally not random, but targeted.
>
> But the basis of the targeting (the sampling frame, and the manner in
which the sample is selected from the sampling frame) is highly
variable, and the execution of it is challenging and highly error-prone.
>
> One result is that within-country case-counts aren't comparable over
even short periods, let alone the whole 4-8 weeks to date.
>
> A second result is that inter-country comparisons are completely
meaningless, because the confounding variables dominate the data.
It suits the media to keep reporting numbers and dressing them up in
graphics of various kinds. And, to bolster the credibility of their
graphics, they need to boost the mythology of modellers. But the
informational value of case statistics is at about the same level as the
'what the celebrities did yesterday' pages.
Hopefully the policy-makers know all this, are ignoring the simpletons,
are taking into account insights drawn from multiple partial models that
deliver bits and pieces of insights into segments of the whole problem
(Bernard's "multiple, interconnected models fed by real-life, current
data"), and are making progressive and adaptable judgement calls based
on what they have available to them at the time.
--
Roger Clarke mailto:[email protected]
T: +61 2 6288 6916 http://www.xamax.com.au http://www.rogerclarke.com
Xamax Consultancy Pty Ltd 78 Sidaway St, Chapman ACT 2611 AUSTRALIA
Visiting Professor in the Faculty of Law University of N.S.W.
Visiting Professor in Computer Science Australian National University
_______________________________________________
Link mailing list
[email protected]
http://mailman.anu.edu.au/mailman/listinfo/link
