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What Next | Daily News and Analysis

Our Year: Emergency Mode Can’t Last Forever

What Next | Daily News and Analysis

Slate Podcasts

Daily News, News, News Commentary

4.32.4K Ratings

🗓️ 17 March 2021

⏱️ 27 minutes

🧾️ Download transcript

Summary

The COVID-19 pandemic exposed crucial gaps in the public health system, including the government’s inability to gather data quickly and accurately. After a year of lockdowns and isolation, a return to life resembling normalcy is in sight, but how will we know when we get there?  Guests: Alexis Madrigal, co-founder of The COVID Tracking Project, and staff writer at The Atlantic. Slate Plus members get bonus segments and ad-free podcast feeds. Sign up now. Learn more about your ad choices. Visit megaphone.fm/adchoices

Transcript

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0:00.0

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0:05.9

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0:11.1

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0:20.9

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0:26.9

Slack.com slash DHQ. One of the images I think will stick with me long after this pandemic

0:37.5

is over is the simple visualization that got repeated over and over again, a line graph showing

0:45.3

waves of coronavirus infections, followed by what felt like a tsunami over the winter.

0:50.9

You'd see these graphs when you opened up the newspaper and they'd get blasted out

0:55.3

over Twitter. And the data many of these charts were based on. It came from one source,

1:01.7

the COVID tracking project. I wonder if you'll ever look at a line graph the same way again,

1:07.7

because I feel like I close my eyes and I see the sort of waves of coronavirus and that

1:14.5

must go double for you. Yeah, it is interesting. Like any certain

1:21.3

shapes of charts, like I definitely am like, oh, I know that one.

1:25.6

Alexis Madrigal runs the COVID tracking project with his colleagues over the Atlantic magazine.

1:33.1

He's a journalist there. And last year he was looking for information no one seemed to

1:37.5

have, which is how he ended up recruiting a bunch of volunteers to track it down, state-by-state.

1:43.3

He was looking for COVID testing and infection numbers, hospitalization rates, death data.

1:50.3

And what they found was a bit of a mess. Each state was doing it their own way, feeding

1:56.1

dribbles or day looses of information to an unsuspecting public.

2:01.3

It's funny. I do think that it has changed my relationship to the idea of data a little

2:05.7

bit. It has not led me to believe that data is like all-knowing or powerful or something

...

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