This post is primarily for my Poli381 students. It is a collection of resources I have come across wherein people are using data analytical techniques to understand, communicate about, and fight the COVID-19 outbreak.
- Very impressive visualization to illustrate spread of the virus, by country. The underlying visualizations here are done in R, and the author is making all the files available here.
- Similar thing here. Also done in R.
- An experiment on how to slow down the spread of misinformation about the disease.
- Nicely formatted data on infections and deaths, updated daily. (This is what I was going to use for the final project, if we had gone that route.)
- This is a contrarian take that kinda argues that we’re overreacting. Ioannidis is a prominent statistician and has a good reputation. However, a lot of people pushed back on this piece really forcefully, such as here and here and here. Having read this stuff, I think Ioannidis is right that there is a lot of uncertainty about how things will turn out. Our estimates have wide confidence intervals, if you will. And he does a pretty good job laying out some reasons why, using some concepts related to class. BUT he makes a really big leap (too big) to then call the thing a possible fiasco and suggest we should be doing a lot less. See the criticism.
- A poll outlining partisan biases in interpretation of pandemic news.
- Brian Schaffner is examining partisanship in response to the crisis by seeing if Republican-leaning areas are less likely to do Google searches for “hand sanitizer” than Democratic-leaning areas. Here are his figures, procedures, and code.
- Nice rundown of a lot of stuff, including some of the above, from the NY Times.
- This is just a fantastic visualization of the trends–best one I’ve seen. Helpfully, it focuses on deaths, rather than diagnoses (wherein the trends are hugely confounded by the availability of tests). And it uses a logarithmic scale and has useful reference lines.
- County-level data from the NY Times.
- Paper attempting to estimate the effects of temperature and humidity on transmission rates.
- Facebook releases data resources to help researchers assess the effectiveness of social distancing measures.