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<p>It seems like estimating/tracking R(t) is key to re-opening
(LIBERATE!) strategies.</p>
<p><br>
</p>
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cite="mid:55fbead1-ef56-813a-20be-5e4891461a09@swcp.com">
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<p>This just in via Josh Thorpe.</p>
<p>I've been wondering if anyone had a methodology for calculating
the COVID19 R <i>Replication Number.</i><br>
</p>
<blockquote>
<p><a href="https://rt.live/" moz-do-not-send="true">https://rt.live/</a></p>
</blockquote>
<p>apparently adapted from our own (LANL) Luis Bettencourt's work
on H5N1 using a Bayesian approach<br>
</p>
<blockquote>
<p><a
href="https://github.com/k-sys/covid-19/blob/master/Realtime%20R0.ipynb"
moz-do-not-send="true">https://github.com/k-sys/covid-19/blob/master/Realtime%20R0.ipynb</a></p>
</blockquote>
<p>This notebook is pretty big and pretty dense, I'm trying to
skim through it and get a feel for it.</p>
<p>It appears superficially that they are using nothing more than
reported new cases smoothed by a Gaussian filter to remove
reporting/test/delay artifacts.</p>
<p>What I'm not clear on quite yet is how (if) this approach
handles the intrinsic delay between exposure and onset of
symptoms sufficient to yield a confirmed case? If that
(variable) delay is not factored in then the R(t) would seem to
be a smeared reflection of R(t-n...t) where "n" is the maximum
number of days between exposure and confirmation. I'll keep
looking.</p>
<p>I wish the summary view had a time-slider to watch the states
R(t) evolve... the buttons included for different previous times
(yesterday, last week, 2 weeks, 3 weeks) give a hint of this.</p>
<p>I'm surprised at how high some of the R values were even over
4.0 for some states at some time.</p>
<p>I'm also surprised at how many states seem to have dropped
to/below 1.0. And also how many seem to have dipped below 1.0
and bounced back up. This would seem to imply that many states
hit a high level of social distancing/hygiene and then relaxed
it (recently?).</p>
<p>I also haven't sussed out why the different states have such
different error envelopes...</p>
<p>I look forward to others possibly digging into this and sharing
their observations.</p>
<p>- STeve<br>
</p>
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