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<p>Glen -</p>
<p>Very interesting view on these three counties... numbers
normalized to population count and population density are a "good
start"!<br>
</p>
<p> The question of what a good "mixing model" is for different
geopolitical demographics is fascinating. It seems like
McKinley/Gallup is on one end of the spectrum (very low population
density overall, but a strong concentration in *one* location (or
small set of service/shopping locations IN Gallup) serving the
whole county population) vs Bernalillo which has dozens of
sub-communities where their sub-populations may stay "close to
home" if not always "at home", shopping at one or two of their own
neighborhood supermarkets/hardwares. <br>
</p>
<p>Poverty (and rurality) may also correlate positively with delays
in diagnosis. More people may be more used to just staying home
and weathering out an illness since going to the doc or urgent
care can have a significant hurdle financially and logistically (a
tank of gas, requiring the only reliable family vehicle, etc).
I'm assuming that the "diagnosed case" date is not the presumed
date of exposure/contraction/onset-of-symptoms but rather the date
of the return of a test or of a declaration of a health-care
worker.</p>
<p>- Steve<br>
</p>
<blockquote type="cite"
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<pre class="moz-quote-pre" wrap="">Based on this discussion, I divided by population (per county, not a normalized amount like 100k) and land area (not including water area). The results are interesting. There was a report about a Gallup hospital having problems. So, I used McKinley county (NM) for comparison.
The raw slopes still (I think) do the best to show what's happening. Dividing by population biases the data to magnify the low population county. Dividing by area magnifies the smaller counties (Bernalillo: 3k km^2, Santa Fe: 5k km^2, McKinley: 14k km^2). Dividing by both produces the same "phenotype" as the simple Δ's, but squashes out the profile shapes (e.g. the slight sigmoid in the Bernalillo slope).
My standard mix with DeKalb, King, & Denver (and now Hall as well) shows even more interesting behavior, dividing out both population and area how Hall has caught up with Denver (a really bad sign since Denver County is very dense, mostly just the city of Denver and the airport, an order of magnitude denser than Hall). But i won't spam the list with this stuff anymore.
On 5/6/20 3:13 PM, uǝlƃ ☣ wrote:
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<pre class="moz-quote-pre" wrap="">I think Δcases/m^2 would be interesting.
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