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The Mole's Favorite SARS-Cov-2 Links
06/11/20
- Worldometers (https://www.worldometers.info/coronavirus/#countries)
- 91-DIVOC (http://www.91-divoc.com/pages/covid-visualization/), the best way to monitor on a log scale. Looking at NY and CA on the US State-level data and switching between log and linear is a great way to build intuition about the math of flattening the curve.
- SF Chronicle tracker (https://projects.sfchronicle.com/2020/coronavirus-map/), a quick reference for the daily Bay Area numbers.
- USA Facts (https://usafacts.org/visualizations/coronavirus-covid-19-spread-map/), an excellent county-level visualization across the US.
- NYT (https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html), another county-level visualization, with commentary.
- Johns Hopkins (https://coronavirus.jhu.edu/map.html), the go-to source for global information
- Our World in Data (https://ourworldindata.org/coronavirus), which has a lengthy and informative explanation of the limits of what we can infer from the data we have.
- Aatish Bhatia's unusual trend analysis (https://aatishb.com/covidtrends/), which intrigues me even though I'm not quite sure how helpful it is. (Watch the Minute Physics video (https://www.youtube.com/watch?v=54XLXg4fYsc) for an intro.)
- COVID Exit Strategy (https://www.covidexitstrategy.org/)
- COVID Tracking (https://covidtracking.com/)
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