Hi everyone welcome to the A6 and Z podcast I'm Sono. Today we're continuing our ongoing

podcast series covering different aspects of the coronavirus pandemic. As a reminder

you can catch all past and recent content on this at a6 and z.com

slash coronavirus. Today's topic is on tracking networks of spread for

predicting pandemics and loads, which has implications for resource

allocation getting back to work and much more. Our guest is sociologist and physician

Nicholas Christakis who directs a human nature lab part of the Yale Institute for Network Science, he and his collaborators previously published work in Ploss on the H1N1 Pandemic, which informed their newly released app,

Hoonala, which is an example of a privacy preserving approach

for tracking pandemics to allow not just rapid warning, but early detection.

They also published a recent paper in nature on how population flow drives spatiotemorial

distribution of COVID-19 in China, end quote, which among other things of all of which is covered in this episode and you can find all the links referenced in the show notes.

Also, a quick note that we have another episode on not just tracking and predicting but the privacy aspects of contact tracing is separate but very related topic on

16 minutes. You can find that show in its own feed if you're not already

subscribed there in your favorite podcast app. In this episode Christakis is interviewed by

A6 and Z general partner Jorge Kante on our bio team. The two also share their

thoughts on how bad is it but they begin with where testing and

tracking fits and what's been missing given that pandemics themselves are a lot

more predictable than most people realize. I need to emphasize just how predictable this is.

It's not just, you know, for example, Bill Gates had this TED Talk in 2015.

Or Tony Fauchy has been publishing papers about this for 20 or 30 years.

I could reach over on my bookshelf right here

and get a book called National Strategy for Influenza Pandemic.

...