How Are We Doing with COVID-19 in the U.S. Right Now? (Take 3)

Update: More recent iterations are available:

Many thanks to all of the feedback about my latest attempt to make sense of the Coronavirus pandemic. I listened, and I played, and I learned, and I now have a new graph that I think better represents how the U.S. is doing:

This is a semi-logarithmic graph of daily new cases over time. I’m comparing the U.S. (blue and bold), China (red), South Korea (yellow), and Italy (green). I’ll explain the changes I made from last time below, but first, three quick takeaways:

First, don’t trust my analysis. I’m an amateur at this, my math is incredibly rusty, and it turns out that my statistics (which were always suspect) are even more suspect than I thought. Critiques, corrections, and constructive discussion encouraged!

Second, don’t passively consume what you read. This started off as a quick exercise to try to make sense of the craziness. It’s led to lots of encouragement, but also lots of (welcome) critiques, which has helped me sharpen my analysis, correct some assumptions, and feel like I have a better grasp of what’s going on and how to assess other things I read. I feel a lot better than I did a few days ago

Third, the U.S. isn’t doing great right now. Our line is more or less tracking China, Korea, and Italy’s initial growth rate, but both China and Korea had started slowing their growth rate about a week before we did. Our curve is looking a lot more like Italy’s, which does not speak well of the weeks ahead here.

Here are the changes I made from last time:

First, I switched over to a semi-logarithmic graph. Hat tip to Ken Chase for encouraging me to do this and to Matt Bruce for this pointer as to why this is important.

When I originally started mapping this out, I didn’t think that the semi-logarithmic graph would tell me much more than the linear graph did. Italy was off the chart, which was all I felt like I needed to know, and I felt like I could make sense of the rest of the curves on the chart. Still, after receiving this feedback, I decided to try the semi-logarithmic version to see what I would learn. As you can see above, my conclusion changed quite dramatically. We in the U.S. are not doing well right now. You can see that the slope of our graph tracks quite closely with Italy.

The other (more math-y) benefit is that I can measure the slope of the line (0.15), which gives me the rough power law for how viral Coronavirus has been in both the U.S. and Italy (y = 100.15x). China and Korea’s containment slope (-0.1) provides the rough power law for the potential impact of containment (y = 10-0.1x). You can use these equations to model out different scenarios (which my friend, Charlie Graham, has been doing).

Second, I’m no longer normalizing by population. Two people questioned whether or not this was useful. (Thank you, Majken Longlade and Corey O’Hara.) Their argument was that normalizing by population doesn’t tell you much in the case of epidemics, because transmission and virality are more a function of closeness and density. The U.S. is a huge country geographically compared to Korea or Italy. The better approach would be to try to normalize based on population of regional outbreaks.

I agree, and I’d like to try to do this. The data is a lot harder to come by, but I think it would be possible to manually pull together with a little bit of elbow grease, especially if we’re constraining the countries where we’re trying to do this. (Leave a comment below if you’d be interested in trying this.)

(Side note: I am extremely grateful for the wide availability of data and for all the people doing an incredible job of analyzing and sharing. This is no accident. A lot of folks have invested an incredible amount of time and energy over the past two decades advocating for the open web and open data, all of which is required to make this work. This becomes even more clear when realizing what’s missing. Martin Cleaver asked me to include Canada in my graph. Easy enough, I thought. Turns out it’s not. Canada doesn’t make this data available. Majken shared this article that explains Canada’s situation.)

Nevertheless, I thought it was still useful to look at data normalized by population. My reasoning was that, at worst, it wouldn’t make the data worse, and, at best, it might make it better. I decided I would try to test this assumption by comparing the graphs of the normalized data with the non-normalized data above:

Again, I think switching to a semi-logarithmic graph made a difference, because if you compare these to graphs, the slopes (which I’m most concerned about) are largely the same. Normalizing the data doesn’t impact the slopes. On the one hand, my assumption was correct — normalizing didn’t seem to hurt the data. On the other hand, it also didn’t tell me anything new, either. So, I decided to stop normalizing and stick with the data as is. (I’d still like to try normalizing by outbreak region, though.)

One point that came up often was that these graphs don’t take into account the underreporting in the U.S. due to lack of testing. I tried to take this into account in my very first sketch, as I mentioned in my original blog post. However, I decided to move away from this for a few reasons. First, every country is underreporting. It didn’t feel useful to add in hand-wavy multipliers. Second — and this is where the semi-logarithmic graph again comes to the rescue — adding a multiplier won’t change the slope, which is what I’m really interested in. It just moves the curve up or down.

Remember, these are all lagging indicators anyway. In all likelihood, any changes we make today won’t be reflected for at least a week. What’s done is done. The best thing we can do right now is to be as proactive as possible, given the circumstances. If we’re going to implement policies like Italy has, it’s better that it happens today than a week from now. Public policy aside, there is one thing we all can do that will absolutely make a difference: STAY HOME!

One more aside: My friend, Greg Gentschev, has often said that the best thing we can do to become better systems thinkers and doers is to learn how compounding works. (Turns out that the physicist, Albert Allen Bartlett, said this too. Great minds!) Maybe one of the positive outcomes of all this is that this will start to happen. I’ve seen two great resources for this so far. One is the Washington Post’s Coronavirus Simulator, which they published yesterday. The other is this video on exponential growth and epidemics. (Hat tip to Nicky Case and James Cham.)

Many thanks to Martin Cleaver and Matt Bruce for sharing my previous blog post, which led to a lot of the discussion that shaped this latest iteration. And many thanks to all who have engaged with this so far. Stay home, wash your hands, and take care!

Charles and Ray Eames on Design

Charles Eames’s diagram explaining the design process. From the Oakland Museum of California’s outstanding Charles and Ray Eames exhibit.

I saw the Charles and Ray Eames exhibit at the Oakland Museum of California this past weekend. (Thanks to James Cham for prolifically tweeting about it. It was really, really good.) Among the many highlights was this 1972 interview on design. It’s short and sweet, and you should read the whole thing. Here are my favorite excerpts:

What is your definition of “Design,” Monsieur Eames?

One could describe Design as a plan for arranging elements to accomplish a particular purpose.

Is Design an expression of art?

I would rather say it’s an expression of purpose. It may, if it is good enough, later be judged as art.

Is it a method of general expression?

No. It is a method of action.

Is Design a creation of an individual?

No, because to be realistic, one must always recognize the influence of those that have gone before.

Is Design a creation of a group?

Very often.

Is there a Design ethic?

There are always Design constraints, and these often imply an ethic.

Does Design imply the idea of products that are necessarily useful?

Yes, even though the use might be very subtle.

Is it able to cooperate in the creation of works reserved solely for pleasure

Who would say that pleasure is not useful?

To whom does Design address itself: to the greatest number? to the specialists or the enlightened amateur? to a privileged social class?

Design addresses itself to the need.

Doug Engelbart, Human Systems, Tribes, and Collective Wisdom

Sunday, December 9 was the 50th anniversary of Doug Engelbart’s The Mother of All Demos. There was a symposium in his honor at The Computer History Museum and much media and Twitter activity throughout.

Among the many things said and written that caught my eye that weekend was a Twitter exchange between Greg Lloyd and Mark Szpakowski. Greg tweeted a quote from this Los Angeles Review of Books article:

“At the very heart of Engelbart’s vision was a recognition of the fact that it is ultimately humans who have to evolve, who have to change, not technology.”

Mark responded:

And yet 99% of the Engelbart tribe work has been on the techie Tool System. http://www.dougengelbart.org/firsts/human-system.html … used to say “coming soon”; now it has disappeared. Time to join up with recent progress on Social Technologies for Complex Adaptive Anticipatory Human Systems?

I agree with Mark, with one caveat: It depends on how you define the “Engelbart tribe.” Let’s explore this caveat first.

Tribes and Movements

There are many folks specializing in process design (what Doug would have categorized as “Human Systems”) who consider Doug a mentor or, at worst, an inspiration. I’m one of them, although I didn’t start (exclusively) from this place when I started working with him in 2000.

Three others in this group have been direct mentors to me: Jeff Conklin, who spent a good amount of time with Doug, and Gail and Matt Taylor, who didn’t, but who knew of him and his work. David Sibbet, the graphic facilitation pioneer, came across Doug’s work in 1972 and worked some with Geoff Ball, who was on Doug’s SRI team doing research on facilitating groups with a shared display. Those four people alone make for an impressive, accomplished, world-changing group.

There are also many, many more folks doing important work in human systems who aren’t familiar with Doug’s work at all or who don’t identify with him for whatever reason. Doug himself thought that lots of what was happening in both open source software development communities and in the Agile Movement were highly relevant, although he had nothing to do with either. At the Symposium celebrating Doug, Christina Engelbart, Doug’s daughter and the keeper of his intellectual legacy, connected the Lean movement to her dad’s work and invited Brant Cooper, the author of The Lean Entrepreneur, to speak.

An effective movement is an inclusive one. What matters more: Seeing Doug’s vision through, or establishing tribal boundaries? If the former, then it’s important to acknowledge and embrace the work of those who may not have the same heroes or conceptual frames of reference.

I don’t think many of us who loved Doug and were inspired by his vision have been very good at this, and unfortunately, our tribalism has extended to technologists too. After the Symposium, I had drinks with my friend, James Cham, who is a long-time fan of Doug’s, but who wasn’t lucky enough to spend much time with him. James told me that Dylan Field (co-founder of Figma Design) was inspired by Doug and that he had hosted his own celebration of the Demo that same Sunday that 300 people attended. Amjad Masad (founder of Repl.it, a tool that Doug would have loved) gave a thoughtful toast about Doug’s work there.

I didn’t know either Dylan or Amjad, and I certainly didn’t know that they tracked Doug’s work and were inspired it. I’m fairly certain that the organizers of the official celebration didn’t either. That’s pretty remarkable, given how small of a place Silicon Valley is. Now that we know, I hope we can start making some fruitful connections.

Capabilities and Collective Wisdom

The movement of folks committed to Doug’s larger vision is much larger than the “official” tribe to which Mark referred in his tweet. But even if we take into account this larger group, I think Mark’s criticism still holds.

Doug sought to make the world collectively smarter. He believed the path to achieving this would be a co-evolutionary process involving both tool and human systems. In other words, new tools would give us new capabilities, assuming we learned how to master them. Those new capabilities would inspire us to create even better tools. Rinse, and repeat.

As my friend, Travis Kriplean, pointed out to me this morning, we can already test this hypothesis. Technology has already evolved exponentially. Have our collective capabilities — or even more importantly, our collective wisdom — evolved with it?

Let’s narrow the question. Our ability to capture, store, and share information has improved by leaps and bounds since Doug’s Demo in 1968. Has our collective memory increased as a result of that?

If you were pinning me down, I would guess, “no.” The mere existence of those tools don’t guarantee that we remember more. Furthermore, the tools have a nasty side effect of overwhelm. But, these tools certainly create the potential for us to remember more — we just have to figure out how.

Right now, my eight- and 14-year old nephews have access to this blog, where they can read many of my innermost thoughts, including stories I wrote about them when they were younger. Right now, they can explore my Flickr, Instagram, and YouTube accounts without even having to ask for permission. If they asked for permission, I would probably let them go through my Google Maps Timeline, which is automatically harvested from my cell phone’s location data and which contains a comprehensive journal of my every day travels over the past few years. They already have access to lots of information about me, including my efforts to distill little bits and pieces of my experience. Most of this is purely the result of technology, with a little bit coming from my occasional discipline of sharing thoughts here and there.

But does any of this help them become wiser? If not, is it because our technology has not evolved enough, or is it because our human practices have not evolved with the technology?

The best example I know of a human system that evolved with the technology are wikis in general and Wikipedia in particular. Not enough people realize that wikis and Wikipedias aren’t just tools. They are a wonderful marriage of human and tool systems that created fundamentally new collective capabilities, exactly the type of thing that Doug envisioned. They are also 20-year old examples. I think this speaks very much to Mark’s critique.