Thread by @DinaPomeranz

Today I added a few slides about Covid-19 to the beginning of the "Global Policy Analysis" class, before delving into the regular material. Students expressed appreciation that we took time to do that. @adinarom encouraged me to share it here in case it's useful for others.

1/n

We first took an anonymous vote, so that I could get a sense of where students were at regarding the topic:

It turned out the majority response was 2), with the smallest response going to 1).

2/n

We then started by looking at recent numbers of confirmed cases & how they have evolved in a steep increasing slope in most countries.

Looking at absolute numbers, Switzerland doesn't look so high. But we are a small country. In per capita terms, we are actually the 2nd highest:

We then discussed that the key here is not the current number, but the trajectory. Switzerland (highlighted in blue) is currently on a trajectory of doubling roughly every 2 days. This figure is on a log scale, so the numbers become staggeringly high very quickly.

This and most of the other images in these slides are from the excellent website ourworldindata.org/coronavirus which is very regularly updated with the newest numbers. It includes many different countries, so in the original you can highlight countries other than Switzerland.

5/n

We talked about exponential growth patterns, and why they tend to be so intuitive for most people.

6/n

We then discussed caveats and measurement issues of infection rates, and how detected infections are both a result of infection rates and testing rates, making comparison across countries difficult.

7/n

So we looked at mortality numbers, which may potentially suffer from somewhat less measurement error, given that they are much more likely to be detected than e.g. mild Covid-19 infections.

The growth rates again are staggering & worldwide currently on a very steep slope.

8/n

So we discussed the importance of flattening this curve. As many of us have now heard many times, it is important to slow down the growth, so that at its peak, the epidemic does not overwhelm the health care system.

There are two more reasons why flattening the curve matters so much:

-It gives us time to learn how to best treat severe cases. The later someone gets sick, the better we can treat them.

-With time, the likelihood grows that scientists can develop a vaccine & medication.

10/n

Why we *really* care about keeping the health system from becoming overloaded

11/n

How can we flatten the curve?

The key is to reduce the transmission chains by any means --> avoid physical distance with other people. If we do interact with other people, washing our hands immediately after thoroughly for 20 seconds.

12/n

Why does this matter so much? Because the more people we meet, the more likely the virus is to spread.

And the numbers go up fast. As of March 13th, in a group of 20 people there was already a 1 in 5 chance of one person having the virus (source @AguzziTemp).

13/n

What are the symptoms? Mostly fever and cough. But some people have neither of them.

14/n

Most cases are actually mild.

But a sizeable share is severe or critical, and these are the cases we worry about.

15/n

Who is most at risk? Those with underlying health conditions and the elderly. After the age of 60, mortality rates increase drastically.

(Here estimated numbers from China)

16/n

The students are young. So why worry?

Because young people can be a source that spreads the virus far & wide. Young & healthy have a big responsibility.

Even if we don't directly meet people in vulnerable groups, through the network of contacts the virus will reach them.

17/n

How big will this get?

A lot about it is still very uncertain. But the mortality rate seems to be an order of magnitude higher than that of flu, and the spread much wider.

Even under assumptions that aren't crazy, this could lead to potentially very high number of deaths.

18/n

We really want to avoid these scenarios & that's why many governments have now taken drastic steps.

This is a classic case of a negative externality, where the behavior of one person affects the wellbeing of another. Therefore "self-responsability" or markets won't fix it.

19/n

Time to panic? No. But time to take it very seriously.

Avoid any gatherings, only leave the home when really necessary. Ideally choose a small group of people with whom you interact & interact with those exclusively

Keep washing your hands thoroughly after any interaction

20/n

Ideally, we sort into two groups:
- those who interact with elderly persons or members of vulnerable populations to support them, and with nobody else
- and those who interact with other people, e.g. children, and do not interact with elderly persons at all.

21/n

While we keep physical distance, we can still have fun! Time to be creative and invent new ways of coming together without physically meeting.

#AloneTogether Zoom happy hours or dinner parties, etc.

Let's stay socially close while being physically distant!

22/n

For more information about much of the content in these slides, I warmly recommend ourworldindata.org/coronavirus. It has interactive figures where you can look at different countries and time periods.

In next class, we'll talk a bit about the economic ramifications of Covid-19.

/end

Ps. If anyone wants a copy of the powerpoint slides to edit and use for your own class, just send me an email!

Since someone asked via email: of course I can also send you the slides for personal use for your relatives, friends, etc.! The more people understand these issues, the better.

I just realized that I can post the link to Dropbox and anyone can just access them directly. dropbox.com/s/ylig3xj505py…