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*From*: bernard cleyet <bernardcleyet@redshift.com>*Date*: Mon, 20 Apr 2020 01:29:56 -0700

On 2020/Apr/19, at 16:03, John Denker via Phys-l <phys-l@mail.phys-l.org> wrote:

A good starting place

is to assume that R₀ is piecewise constant, punctuated

by changes in public policy.

I’ve thought of relating the changes in improvement in policy w/ changes in the doubling time, or more easily seen as the slope of the cumulative cases in a log plot. I suppose it should be ~ five days after the effective implementation. Using this I’ll look at some of my plots; for deaths more likely fifteen days?

In searching for Re. Rho effective I found these: https://web.stanford.edu/~jhj1/teachingdocs/Jones-on-R0.pdf and https://en.wikipedia.org/wiki/Basic_reproduction_number.

As an example of how sensitive the simplest model from cases, I’ll put in http://cleyet.org/covid-19/USA/California/Monterey%20county/. The last week of published data were corrected upwards from a mean 2.4 daily cases to 6.1. This moved the peak forward two weeks.

bc. of necessity, simple minded.

p.s. The sigmoid formula I use is the intermediate in the number of coefficients offered by KaleidaGraph.

**References**:**[Phys-L] Confessions of a Repentant Modeler in a Time of Plague.***From:*brian whatcott <betwys1@sbcglobal.net>

**Re: [Phys-L] Confessions of a Repentant Modeler in a Time of Plague.***From:*David Bowman <David_Bowman@georgetowncollege.edu>

**Re: [Phys-L] Confessions of a Repentant Modeler in a Time of Plague.***From:*John Denker <jsd@av8n.com>

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