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<p class="MsoNormal">And don’t tell me it is too expensive to send out test kits! All people would have to do is scan a QR code on TV and be directed to an app that would check if their phone was compatible with the test kit machinery. Lord knows they
would be *<b>motivated</b>* to figure it out. Sure this would take a lot of planning and infrastructure, but supposing there was federal leadership, it could be done. And no it wouldn’t get everyone, but it could get millions of people (to get good statistics)
to inform public health decisions Perhaps the sample test kit could be returned so that the users’ full genome could be sequenced. Again, not everyone would be willing to do that, but I bet a lot would. (Oh no, instead we have Birx stare at her feet
while the moron talks about intubating people with UV lights.)<o:p></o:p></p>
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<p class="MsoNormal"><b><span style="font-size:12.0pt;color:black">From: </span></b><span style="font-size:12.0pt;color:black">Friam <friam-bounces@redfish.com> on behalf of Marcus Daniels <marcus@snoutfarm.com><br>
<b>Reply-To: </b>The Friday Morning Applied Complexity Coffee Group <friam@redfish.com><br>
<b>Date: </b>Sunday, April 26, 2020 at 12:53 PM<br>
<b>To: </b>The Friday Morning Applied Complexity Coffee Group <friam@redfish.com><br>
<b>Subject: </b>Re: [FRIAM] Mawdel Tawk<o:p></o:p></span></p>
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<p class="MsoNormal">I think the modeling without priors occurs because of the failed surveillance. If there had been aggressive testing, contact tracing, and quarantining, the spread might be have been stopped, but, even if it were not, at least there would
be case history stories that could be put into an agent-based model. Are spread rates on the subway different than at churches and sports events or Mardi Gras? There was no competent effort to do that, so modelers like Murray’s team fish for explanatory
variables retrospectively. Such models could probably make precise predictions if millions of people had test kits arrive in the mail the first week, and Apple and Google coordinated to have them relay diagnosis information (via smartphones) to a central
repository.<o:p></o:p></p>
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<p class="MsoNormal"><b><span style="font-size:12.0pt;color:black">From: </span></b><span style="font-size:12.0pt;color:black">Friam <friam-bounces@redfish.com> on behalf of "thompnickson2@gmail.com" <thompnickson2@gmail.com><br>
<b>Reply-To: </b>The Friday Morning Applied Complexity Coffee Group <friam@redfish.com><br>
<b>Date: </b>Sunday, April 26, 2020 at 11:33 AM<br>
<b>To: </b>'The Friday Morning Applied Complexity Coffee Group' <friam@redfish.com><br>
<b>Subject: </b>[FRIAM] Mawdel Tawk</span><o:p></o:p></p>
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<p class="MsoNormal">Dear Wizards, <o:p></o:p></p>
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<p class="MsoNormal">I commend to your attention a blog post from 538 in which Nate Silver talks with the guy who leads the University of Washington health metrics modeling operation. I understood barely one word in five, but the chief difference between them
seems to be on the degree to which they rely on priors or curve fitting. You folks will, I predict, know what that means. Don’t hesitate to explain it to me.
<o:p></o:p></p>
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<p class="MsoNormal"><a href="https://podcasts.apple.com/us/podcast/model-talk-forecasting-the-toll-of-covid-19/id1077418457?i=1000472325708">https://podcasts.apple.com/us/podcast/model-talk-forecasting-the-toll-of-covid-19/id1077418457?i=1000472325708</a><o:p></o:p></p>
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<p class="MsoNormal">Nick <o:p></o:p></p>
<p class="MsoNormal"> <o:p></o:p></p>
<p class="MsoNormal">Nicholas Thompson<o:p></o:p></p>
<p class="MsoNormal">Emeritus Professor of Ethology and Psychology<o:p></o:p></p>
<p class="MsoNormal">Clark University<o:p></o:p></p>
<p class="MsoNormal"><a href="mailto:ThompNickSon2@gmail.com">ThompNickSon2@gmail.com</a><o:p></o:p></p>
<p class="MsoNormal"><a href="https://wordpress.clarku.edu/nthompson/">https://wordpress.clarku.edu/nthompson/</a><o:p></o:p></p>
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