My New Favorite COVID-19 Dashboard

TL;DR I’m now using this dashboard as a way to make sense of what’s happening with COVID-19. It’s still too soon to draw any conclusions about how well the U.S.’s interventions overall are working.

I started trying to make sense of the COVID-19 growth rate data myself on March 13, 16 days ago. I learned a lot along the way, and my daily ritual of looking up numbers and updating my spreadsheet has been strangely calming. Here’s my latest graph:

Three observations when comparing this to last week’s graph:

  1. Italy’s growth rate seems to be flattening, which is a positive sign
  2. U.S.’s growth curve continues to rise at a steady rate; more on this below
  3. Even though China and Korea’s growth rates have been steady for a while now, it’s not zero. They have this under control (for now), but it’s far from over, and it won’t be until we have a vaccine, which folks keep saying is at least 12-18 months away.

My friend, Scott Foehner, chided me last week for saying that the results are lagging by about a week. He’s right. Based on Tomas Pueyo’s analysis (which I cited in my original blog post), the lag is more like 12 days. This is why the Bay Area shelter-in-place ordinance was for three weeks — that’s how much time you need to see if you’re containing your growth rate.

Shelter-in-place in the Bay Area started on March 17, exactly 12 days ago and four days after I started tracking. California’s order started on March 20. Other states followed after that, but not all.

It’s hard to make sense of all this when aggregated as a country. I’ve been wanting regional data for a while now, but have felt too overwhelmed to parse it out myself. Fortunately, other people have been doing this.

One of the positive outcomes of me doing this for myself for the past few weeks is that it’s given me a better sense of how to interpret other people’s graphs, and it’s helped me separate the wheat from the chaff. It’s also made me realize how poor data literacy seems to be for many media outlets, including major ones. They’re contributing to the problem by overwhelming people with graphs that are either not relevant or are not contextualized.

One media outlet that’s been doing a great job, in my opinion, has been The Financial Times, thanks to John Burn-Murdoch. Inspired by John’s work, Wade Fagen-Ulmschneider has produced this excellent dashboard, which has provided me exactly what I’ve wanted. (Hat tip to Rashmi Sinha.) I may stop updating my spreadsheet as a result, although I might miss the ritual too much.

Wade’s dashboard is pretty configurable overall, although you have limited control over which region’s data you’re showing. Here’s the closest equivalent to what I’ve been tracking:

And here’s what I’ve really wanted to see: the state-by-state data:

What does this tell us about the interventions so far? Again, not much. It’s too soon. Check back in another week.

I’ve seen some articles floating around with graphs comparing California to New York, crowing that sheltering-in-place is already working here. That may be the case, but it’s still too early for us to know that, and it’s irresponsible to point to a chart and suggest that this is the case. There are lots of reasons why New York might be doing so poorly compared to California that have nothing to do with interventions, density being the obvious one. Regardless, history has proven that even a few days can make a huge difference when it comes to containing epidemics, and I feel incredibly grateful that our local leaders acted as quickly as they did.

I think there are two questions that are on people’s minds. One is about hospital capacity. I’ve seen various attempts to model this, including the Covid Act Now site I mentioned last week. The one I find easiest to browse is this dashboard from the Institute for Health Metrics and Evaluation. They publish their model, which I haven’t even attempted to parse yet. (I doubt that I have the expertise to evaluate it anyway.) It suggests that, even if our current measures have flattened the curve in California, we’ll still exceed our capacity of ICU beds needed in about two weeks, although we should be okay in terms of general hospital capacity.

The second question is how much longer we’ll need to shelter-in-place (or worse). Even if we flatten the curve, lifting shelter-in-place will just get that curve going again unless we have an alternative way of managing it (e.g. test-and-trace). I haven’t seen any indications of when that will happen, so we’ll just have to continue to be patient. I feel like every day is a grind, and I’m one of the lucky ones. I can’t imagine how folks on the frontlines and those far less fortunate than me are dealing right now.

3 replies to “My New Favorite COVID-19 Dashboard”

  1. For the record, I wasn’t “chiding” you. I was just practicing something I decided to do during the lockdown: engage more on social media 🙂

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